Difference between revisions of "Control with TrackCam Vision Feedback and MATLAB"

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'''Pulses'''<br>
'''Pulses'''<br>
To run these tests, we used Measurement Computing Cards (mcc). Both were installed in the same computer. The MATLAB code that is at the end of this document was then run (testInputOutput.m). It creates an output wave that is a wave of alternating pulses. These were output at a predetermined rate. The input card kept on taking input all the time. Then, the duration of the input pulses was measured to see how long each pulse actually was as opposed to how long we wanted it to be. Plots of this were made, along with the standard deviation and the extra duration of each pulse. Using this method, we were able to see how fast we could feasibly run the alternate pulses without losing accuracy. Figure 1 shows that this test started to break down around 2000 Hz.
To run these tests, we used Measurement Computing Cards (mcc). Both were installed in the same computer. The MATLAB code that is at the end of this document was then run (testInputOutput.m). It creates an output wave that is a wave of alternating pulses. These were output at a predetermined rate. The input card kept on taking input all the time. Then, the duration of the input pulses was measured to see how long each pulse actually was as opposed to how long we wanted it to be. Plots of this were made, along with the standard deviation and the extra duration of each pulse. Using this method, we were able to see how fast we could feasibly run the alternate pulses without losing accuracy. Figure 1 shows that this test started to break down around 2000 Hz.

[[image:numPulses.jpg|thumb|200px|'''Figure 1:''' Number of pulses with given duration.|right]]


===Two Computers===
===Two Computers===
'''Pulses'''<br>
'''Pulses'''<br>
The next step was to output data on one computer and to input data on another. For output, we again used the mcc card. For input, however, we used a National Instruments (ni) card. Two programs were run for this test. The program run from the output computer was testOutput.m, and the one run on the input computer was testInputCard.m. With this simple modification to the setup, the test still ran fine at 10000 Hz, as can be seen in Figure 2.
The next step was to output data on one computer and to input data on another. For output, we again used the mcc card. For input, however, we used a National Instruments (ni) card. Two programs were run for this test. The program run from the output computer was testOutput.m, and the one run on the input computer was testInputCard.m. With this simple modification to the setup, the test still ran fine at 10000 Hz, as can be seen in Figure 2.

[[image:numPulses2.jpg|thumb|200px|'''Figure 2:''' Number of pulses with given duration.|right]]


===Single Computer Again===
===Single Computer Again===
'''Sine Wave'''<br>
'''Sine Wave'''<br>
Following the tests with pulses, we decided to try to send a sine wave instead of a pulse, and to see at what output sample rate the frequency of the wave started to become inaccurate. This test is more practical, since in reality we would be sending sine waves and not pulses, and a little error in the output wave is acceptable in our applications. We used the same single computer setup as before, and ran the code inputOutputSineWave.m. A result of this test can be seen in Figure 3.
Following the tests with pulses, we decided to try to send a sine wave instead of a pulse, and to see at what output sample rate the frequency of the wave started to become inaccurate. This test is more practical, since in reality we would be sending sine waves and not pulses, and a little error in the output wave is acceptable in our applications. We used the same single computer setup as before, and ran the code inputOutputSineWave.m. A result of this test can be seen in Figure 3.

[[image:sineWave.jpg|thumb|200px|'''Figure 3:''' Frequency of sine wave with requested frequency of 50 Hz.|right]]


'''Sine Wave Sweep'''<br>
'''Sine Wave Sweep'''<br>
Finally, we decided to try a sweep of sine wave frequencies to determine exactly where the input frequency breaks down. The code that was run is called sweepOfSampleRatesSineWave.m. The results of this can be seen in Figure 4. This breakdown occurred at 8100 Hz.
Finally, we decided to try a sweep of sine wave frequencies to determine exactly where the input frequency breaks down. The code that was run is called sweepOfSampleRatesSineWave.m. The results of this can be seen in Figure 4. This breakdown occurred at 8100 Hz.

[[image:sweep.jpg|thumb|200px|'''Figure 4:''' Sweep of requested sample rates.|right]]




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===Timing===
===Timing===
The timing of the system is detailed on the timing diagrams. The idea, which is not fully implemented yet, is to have there be two pictures already taken when the MATLAB program calls the MEX-file, so that the program waits for only one more picture to be taken and then grabs all three and processes them all. To implement this, the frame time has to be just a little shorter than half of the total processing time, including the MEX-file processing and the MATLAB processing.
The timing of the system is detailed on the timing diagrams (Fig 5 and 6). The idea, which is not fully implemented yet, is to have there be two pictures already taken when the MATLAB program calls the MEX-file, so that the program waits for only one more picture to be taken and then grabs all three and processes them all. To implement this, the frame time has to be just a little shorter than half of the total processing time, including the MEX-file processing and the MATLAB processing. With a frame time of 500 microseconds, the system keeps up fine and can take pictures at 2000 frames per second. However, tweaking the frame time and exposure time to fit more neatly with processing time can make the system more efficient and perhaps even put the rate to over 2000 Hz, depending on how fast the processing can be done.


[[image:TimingDiagram.jpg|thumb|500px|'''Figure 5:''' Timing Diagram.|left]]
[[image:TimingDiagramDetail.jpg|thumb|500px|'''Figure 6:''' Blowup of Timing Diagram.|right]]

==Next Steps==
In the future, more things can be done to further speed up the system. First of all, using separate cores for the camera and processing may speed up the system as the two tasks would run in parallel. This would require shared memory. Another step that can be taken is to implement all the MATLAB computations in C. This would help because C is quicker than MATLAB and because MATLAB wouldn't have to access the MEX-file every time it wants to take a picture. Also, using a real-time operating system like Linux RTAI would also speed up the process. Stripping down Windows makes it close to real-time, but in reality it is not real-time.


==Code==
==Code==
===Shared Memory===
===Shared Memory===
<nowiki>#include <windows.h>
<nowiki>
#include <windows.h>
#include <stdio.h>
#include <stdio.h>
#include <conio.h>
#include <conio.h>
#include <tchar.h>
#include <tchar.h>


#define BUF_SIZE 256
#define BUF_SIZE 256
Line 158: Line 172:


return 0;
return 0;
}</nowiki>
}
</nowiki>
<br><br>
<br><br>
<nowiki>
<nowiki>
#include <windows.h>
#include <windows.h>
#include <stdio.h>
#include <stdio.h>
Line 221: Line 234:
return 0;
return 0;
}
</nowiki>

===testInputOutput.m===
<nowiki>
clear all
close all
% set a desired sample rate of output
sampRate = 5000;
dt = 1/sampRate;
amp = 1;
% set input card's sample rate
sampRateIn = 50000;
% amount of time to acquire data
timeIn = 10;
trigger = timeIn*sampRateIn;

% creat input and output objects
AI = analoginput('mcc',0);
AO = analogoutput('mcc',1);

% add channels
addchannel(AI,[0:5],[1:6]);
addchannel(AO,[0:5],[1:6]);

% set up cards
set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)
set(AO,'SampleRate',ceil(1/500))

time = 1/sampRateIn:1/sampRateIn:timeIn;
t = 0:dt:timeIn;

% create an output wave that is just an alternating pulse
outputwave = zeros(length(t),1);
for jj = 1:floor(length(t)/2)
outputwave(2*jj,1) = amp;
end
outputwave(:,2) = outputwave;
outputwave(:,[2 3 4 5 6]) = 0;

temp = rand(10);

% start acquisition
start(AI)
tic
a = 0;
% output data
for ii = 1:length(outputwave)
while(toc<(dt*ii))
end
putsample(AO,outputwave(ii,:));
%z = sampleMexFile(ii,ii,ii);
%fft(outputwave);
%fprintf('pause: %f\n',dt-time);
%data(ii,:) = getsample(AI);
end

% collect data
data = getdata(AI);
stop(AI);
delete(AI)
clear AI

% get meaningful data from the channel that matters
meaningfulData = data(:,1);
plot(time,meaningfulData);

freqData = zeros(trigger,1);
counter = 0;
pulseCounter = 1;
% count number of pulses that have a specific duration
for ii = 2:trigger
if (abs(meaningfulData(ii) - meaningfulData(ii-1)) < .05)
counter = counter + 1;
elseif ((counter ~= 0) && (ii-counter > 3))
freqData(counter) = freqData(counter) + 1;
pulseDuration(pulseCounter) = counter/sampRateIn;
counter = 0;
pulseCounter = pulseCounter + 1;
elseif (ii-counter == 3)
counter = 0;
end
end

average = 1/sampRate;
figure
% create a graph of pulse durations
stem(time(1:2*average*sampRateIn),freqData(1:2*average*sampRateIn));
title(['Number of Pulses with Given Duration, Recorded for ',num2str(timeIn),' Seconds (',num2str(sampRate),' Hz)']);
xlabel('Pulse Duration (sec)');
ylabel('Number of Pulses');

averageDuration = 0;
for jj = 1:trigger
if (freqData(jj) ~= 0)
fprintf('%u pulses had duration of: %f \n',freqData(jj),jj/sampRateIn);
averageDuration = averageDuration + (freqData(jj)*jj/sampRateIn);
end
end
fprintf('\n');
averageDuration = averageDuration/sum(freqData);
fprintf('Average duration of pulses: %f \n\n',averageDuration);

standardDev = 0;
% find the standard deviation
for jj = 1:trigger
if (freqData(jj) ~= 0)
for kk = 1:freqData(jj)
standardDev = standardDev + (averageDuration - (jj/sampRateIn))^2;
end
end
end
standardDev = sqrt(standardDev/(sum(freqData) - 1));
fprintf('Standard deviation of duration of pulses: %f \n\n\n',standardDev);

pulseDuration = pulseDuration - mode(pulseDuration);
figure
% plot how much longer or shorter pulses were than what was requested
stem(pulseDuration/dt);
title('Pulse Duration vs. Time')
xlabel('Time (sec)')
ylabel(['Extra length of pulse in terms of dt (',num2str(dt),' seconds)']);
</nowiki>

===testOutput.m===
<nowiki>
clear all
close all
sampRate = 5000;
dt = 1/sampRate;
freq = 30;
timeIn = 30;
amp = 1;

AO = analogoutput('mcc',1);
addchannel(AO,[0:5],[1:6]);
set(AO,'SampleRate',ceil(1/500))

t = 0:dt:timeIn;

outputwave = zeros(length(t),1);
for jj = 1:floor(length(t)/2)
outputwave(2*jj,1) = amp;
end
outputwave(:,2) = outputwave;
outputwave(:,[2 3 4 5 6]) = 0;

tic
for ii = 1:length(outputwave)
while(toc<(dt*ii))
end
putsample(AO,outputwave(ii,:));
%z = sampleMexFile(ii,ii,ii);
%fft(outputwave);
%fprintf('pause: %f\n',dt-time);
%data(ii,:) = getsample(AI);
end
</nowiki>

===testInputCard.m===
<nowiki>
clear all
close all
dt = 1/500;
freq = 30;
sampRateIn = 50000;
trigger = 100000;

time = 1/sampRateIn:1/sampRateIn:trigger/sampRateIn;

AI = analoginput('mcc',0);
addchannel(AI,[0:5],[1:6]);

set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)

start(AI)
data = getdata(AI);
meaningfulData = data(:,1);
plot(time,meaningfulData);

freqData = zeros(trigger,1);
counter = 0;
for ii = 2:trigger
if (abs(meaningfulData(ii) - meaningfulData(ii-1)) < .05)
counter = counter + 1;
elseif ((counter ~= 0) && (ii-counter > 3))
freqData(counter) = freqData(counter) + 1;
counter = 0;
elseif (ii-counter == 3)
counter = 0;
end
end

figure
stem(time,freqData);

for jj = 1:trigger
if (freqData(jj) ~= 0)
fprintf('%u pulses had duration of: %f \n',freqData(jj),jj/sampRateIn);
end
end
</nowiki>

===inputOutputSineWave.m===
<nowiki>
clear all
close all
sampRate = 200;
dt = 1/sampRate;
freq = 50;
amp = 1;
sampRateIn = 50000;
timeIn = 10;
trigger = timeIn*sampRateIn;

AI = analoginput('mcc',0);
AO = analogoutput('mcc',1);

addchannel(AI,[0:5],[1:6]);
addchannel(AO,[0:5],[1:6]);

set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)
set(AO,'SampleRate',ceil(1/500))

time = 1/sampRateIn:1/sampRateIn:timeIn;
t = dt:dt:timeIn;

outputwave = amp*sin(2*pi*freq*t);
outputwave = outputwave';
outputwave(:,2) = amp*sin(2*pi*freq*t);
outputwave(:,[3 4 5 6]) = 0;

start(AI)
tic
a = 0;
for ii = 1:length(outputwave)
while(toc<(dt*ii))
end
putsample(AO,outputwave(ii,:));
z = sampleMexFile(ii,ii,ii);
end

data = getdata(AI);
stop(AI);
delete(AI)
clear AI

meaningfulData = data(:,1);
plot(time,meaningfulData);

[YfreqDomain,frequencyRange] = positiveFFT(meaningfulData,sampRateIn);
positiveFFT = figure;
stem(frequencyRange,abs(YfreqDomain));
xlabel('Freq (Hz)')
ylabel('Amplitude')
title('FFT')
grid
axis([0,2*freq,0,amp])

NFFT = 2^nextpow2(length(meaningfulData)); % Next power of 2 from length of y
Y = fft(meaningfulData,NFFT)/length(meaningfulData);
f = sampRateIn/2*linspace(0,1,NFFT/2+1);
figure
plot(f,2*abs(Y(1:NFFT/2+1)))
title(['Single-Sided Amplitude Spectrum of y(t) (',num2str(freq),' Hz) @ ',num2str(sampRate),' Hz'])
xlabel('Frequency (Hz)')
ylabel('|Y(f)|')
axis([0,2*freq,0,amp])

[a,b] = max(Y(1:NFFT/2+1));
actualFreq = f(b);
fprintf(['\nRequested frequency: ',num2str(freq), ' Hz\n']);
fprintf(['Actual frequency: ',num2str(actualFreq), ' Hz\n']);
</nowiki>

===sweepOfSampleRatesSineWave===
<nowiki>
clear all
close all

freq = 50;
amp = 1;
sampRateIn = 50000;
timeIn = 10;
trigger = timeIn*sampRateIn;

AI = analoginput('mcc',0);
AO = analogoutput('mcc',1);

addchannel(AI,[0:5],[1:6]);
addchannel(AO,[0:5],[1:6]);

set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)
set(AO,'SampleRate',ceil(1/500))

time = 1/sampRateIn:1/sampRateIn:timeIn;

sweep = zeros(100,3);
for sr = 500:100:10000
sampRate = sr;
dt = 1/sampRate;
t = 0:dt:timeIn;

outputwave = amp*sin(2*pi*freq*t);
outputwave = outputwave';
outputwave(:,2) = amp*sin(2*pi*freq*t);
outputwave(:,[3 4 5 6]) = 0;

start(AI)
tic
for ii = 1:length(outputwave)
while(toc<(dt*ii))
end
putsample(AO,outputwave(ii,:));
%fprintf('pause: %f\n',dt-time);
%data(ii,:) = getsample(AI);
end

data = getdata(AI);
stop(AI);

meaningfulData = data(:,1);
NFFT = 2^nextpow2(length(meaningfulData)); % Next power of 2 from length of y
Y = fft(meaningfulData,NFFT)/length(meaningfulData);
f = sampRateIn/2*linspace(0,1,NFFT/2+1);
% figure
% plot(f,2*abs(Y(1:NFFT/2+1)))
% title(['Single-Sided Amplitude Spectrum of y(t) (',num2str(freq),' Hz) @ ',num2str(sampRate),' Hz'])
% xlabel('Frequency (Hz)')
% ylabel('|Y(f)|')
% axis([0,2*freq,0,amp])

[a,b] = max(Y(1:NFFT/2+1));
actualFreq = f(b);
sweep(sr/100,1) = sr;
sweep(sr/100,2) = actualFreq;
end

figure
plot(sweep(:,1), sweep(:,2));
</nowiki>

===integrationTestPutSample.m===
<nowiki>
% This program is a simple control system to test the functionality of the
% camera and actuator closed-loop feedback system. The camera takes
% pictures at a predetermined rate (set in the MEX-file). This program
% accesses the MEX-file and takes the three most recent pictures from the
% image buffer. The coordinates of the centroid of each image are then
% calculated. These coordinates are passed back into this program, where
% the x, y, and z coordinates of the ball are computed and the x and z
% coordinates of the bar are computed. After that, the program checks if
% the ball is below 14.5 mm from the bar. If it is, half a period of a
% sine wave is input into the speakers, and the ball is bounced back up.
% If the previous bounce of the ball was above 21 mm, the amplitude of the
% sine wave is reduced a little. If the pervious bounce was below 19 mm,
% the amplitude of the sine wave is increased a little. This keeps the
% ball bouncing to approximately 20 mm. This loop then runs for as long as
% is specified, and afterwards the space allocated for the images is
% de-allocated.

clear all
close all

% load calibration constants
calib = '8-17-09 Calibration Constants';
load(calib);

% compile the MEX-file
mex -L'C:\PROGRA~1\SiliconSoftware3.2\lib\visualc' -L'C:\Program Files\OpenCV\lib' -ldisplay_lib -lclserme3 -lclsersisome3 -lfastconfig -lfglib3.1 -lfglib3 -liolib -lmenable3 -lhighgui -lcv -lcvaux -lcvcam -lcvhaartraining -lcxcore -lcxts -lml skeleton.cpp cam.cpp imgproc.cpp roi.cpp tracking.cpp utils.cpp
% initialize camera and framegrabber
skeleton(0);

% set the sample rate of the data input into the speakers
sampRate = 2000;
dt = 1/sampRate;
% set the frequency of the sine wave
freq = 30;
amp = 2;
timeOnePeriod = 1/freq;

% create an analog output object
AO = analogoutput('nidaq','Dev3');

% add 2 channels for the two bottom speakers
addchannel(AO,2:3);

% set a sample rate for the output (only matters is the command "putdata"
% is used).
set(AO,'SampleRate',sampRate);

t = 0:dt:timeOnePeriod/2;

% create output wave
outputwave = amp*sin(2*pi*freq*t);
outputwave = outputwave';
outputwave(:,2) = amp*sin(2*pi*freq*t);

% set the length of the loop
lenLoop = 10000;

% initialize vectors to store useful data
height_ball = zeros(1,lenLoop);
height_bar = zeros(1,lenLoop);
proportional = zeros(1,lenLoop);
multArray = zeros(1,lenLoop);
timeArray = zeros(2,lenLoop);
eventTimer = zeros(1,3*lenLoop);
imageNumber = zeros(1,3*lenLoop);
times = zeros(5,lenLoop);

% initialize useful variables
previousHeight = 0;
goingDown = 0;
time_ball(1) = 0;
multiplier = 2;
P = 13.8;
ii = 1;

% start actual control system
while ii<(lenLoop+1)
% access the MEX-file and store results in variable "temp"
temp = skeleton(1);
% use proper entries from "temp" to create inputs for the
% calc_coords3ROI function
XZ = [1 temp(3) temp(1) temp(2)];
YZ = [1 temp(6) temp(4) temp(5)];
bar_tracking = [1 temp(9) temp(7) temp(8)];
%eventTimer((3*ii)-2:(3*ii)) = [temp(3) temp(6) temp(9)];
%imageNumber((3*ii)-2:(3*ii)) = [temp(10) temp(11) temp(12)];
% store the image number, image number modulo 3, time to get first
% image number, time to get rest of images, and time to process images
times(:,ii) = [temp(13); temp(14); temp(15); temp(16); temp(17)];
% calculate coordinates
[XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
% check if bar has to bounce
if XYZ_BALL(5) > 13.9 && XYZ_BALL(5) < 14.5
% check if ball bounced too high
if P > 21
% adjust amplitude of output wave
multiplier = multiplier - .1;
% check if ball bounced too low
elseif P < 19 && multiplier < 4
% adjust amplitude of output wave
multiplier = multiplier + .1;
end
tic
% load output wave into speakers
for kk = 1:length(outputwave)
while(toc<(dt*kk))
end
temp2 = toc;
putsample(AO,multiplier*outputwave(kk,:));
temp = skeleton(1);
XZ = [1 temp(3) temp(1) temp(2)];
YZ = [1 temp(6) temp(4) temp(5)];
bar_tracking = [1 temp(9) temp(7) temp(8)];
%eventTimer((3*ii)-2:(3*ii)) = [temp(3) temp(6) temp(9)];
%imageNumber((3*ii)-2:(3*ii)) = [temp(10) temp(11) temp(12)];
times(:,ii) = [temp(13); temp(14); temp(15); temp(16); temp(17)];
[XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
timeArray(1,ii) = toc - temp2;
height_bar(ii) = XZ_BAR(4);
height_ball(ii) = XYZ_BALL(5);
ii = ii + 1;
if ii>(lenLoop-1)
break
end
end
timeArray(2,ii) = toc;
multArray(ii) = multiplier;
% if ball settles on lens, wait one second and then bounce it back up
elseif XYZ_BALL(5) < 13.9
tic
while XYZ_BALL(5) < 13.9
temp = skeleton(1);
XZ = [1 temp(3) temp(1) temp(2)];
YZ = [1 temp(6) temp(4) temp(5)];
bar_tracking = [1 temp(9) temp(7) temp(8)];
[XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
if toc > 1
tic
for kk = 1:length(outputwave)
while(toc<(dt*kk))
end
putsample(AO,4*outputwave(kk,:));
temp = skeleton(1);
XZ = [1 temp(3) temp(1) temp(2)];
YZ = [1 temp(6) temp(4) temp(5)];
bar_tracking = [1 temp(9) temp(7) temp(8)];
[XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
height_bar(ii) = XZ_BAR(4);
height_ball(ii) = XYZ_BALL(5);
ii = ii + 1;
end
end
end
end
% record the height of the previous bounce
if XYZ_BALL(5) < previousHeight && goingDown == 0
goingDown = 1;
P = previousHeight;
proportional(ii) = P;
elseif XYZ_BALL(5) > previousHeight && goingDown == 1
goingDown = 0;
end
previousHeight = XYZ_BALL(5);
height_ball(ii) = XYZ_BALL(5);
height_bar(ii) = XZ_BAR(4);
ii = ii + 1;
end

% de-allocate memory
skeleton(2);

% make plots of data
figure
plot(height_ball);
title('Height of Ball');
figure
stem(proportional);
title('Max Height of Each Bounce');
figure
stem(multArray);
title('Multiplier');
figure
plot(height_bar);
title('Height of Bar');
% figure
% plot(timeArray(1,:));
% figure
% stem(imageNumber,eventTimer);
% title('Time for Event');

% find average height of bounces
j = 1;
for i = 1:length(proportional)
if proportional(i) ~= 0
temporary(j) = proportional(i);
j = j+1;
end
end
mean(temporary)

% j = 1;
% for i = 1:length(eventTimer)/3
% temporary3(j) = mean(eventTimer((3*i)-2:(3*i)));
% j = j+1;
% end
% figure
% stem(temporary3);
% mean(temporary3)
</nowiki>

===skeleton.cpp===
<nowiki>
/**
* @file skeleton.cpp displays code for a simple one ROI tracker
*
* skeleton.cpp contains the necessary components to start and modify the vision system for
* application-specific tracking/image processing tasks. The code is comprised of three
* functions: set_initial_positions(...), display_tracking(...), and main().
*
* set_initial_positions(...) shows one possible initialization strategy for the camera's
* ROI. This implementation simply takes the known initial position of the object to track
* (the blob) and centers the camera's ROI bounding box around that center.
*
* display_tracking(...) is a sample application of interest for showing (processed) camera
* frames. A function like this also provides visual feedback of what is going on
* internally in the system and is an invaluable debugging tool (see display_run.cpp for
* a more complicated example).
*
* Finally, main() is the starting point of the program. Its role is to initialize the
* camera and run the logic necessary for tracking objects.
*
* Most, if not all, applications will follow this recipe of initialization routines,
* application-specific routines, and finally a main program that sits in a loop acquiring
* the next image to process. A few common setup and helper functions can be found in
* utils.cpp.
*/

#include "fcdynamic.h"
#include "constants.h"
#include "mex.h"

/** Grabs an image from the camera and displays the image on screen
*
* The purpose of this program is to show how to get the camera up and running.
* Modifications can be made by modifying the while(...) loop with different image
* processing and tracking logic.
*/

// important variables used in most applications
int rc;
Fg_Struct *fg = NULL;
TrackingWindow cur[NUM_ROI];
int index = 0;
int seq[] = SEQ;

int takedata = 0; // takedata has value 0 or 1 depending on whether data is being recorded
char key = '0'; // initialize command key
int timeMs; // variable for recording time in microseconds
int inittime; // initial time when data collection begins
int counter = 0; // Counts the number of images taken
FrameInfo timing;
IplImage *cvDisplay[NUM_ROI];

// allocate resources
void initialization(void) {
// following lines are for displaying images only! See OpenCV doc for more info.
// they can be left out, if speed is important.
//IplImage *cvDisplay[NUM_ROI];

#if DISPLAY_TRACKING
cvDisplay[0] = cvCreateImageHeader(cvSize(ROI_BOX_W0, ROI_BOX_H0),
BITS_PER_PIXEL, NUM_CHANNELS);
cvNamedWindow(DISPLAY0, CV_WINDOW_AUTOSIZE);

cvDisplay[1] = cvCreateImageHeader(cvSize(ROI_BOX_W1, ROI_BOX_H1),
BITS_PER_PIXEL, NUM_CHANNELS);
cvNamedWindow(DISPLAY1, CV_WINDOW_AUTOSIZE);

cvDisplay[2] = cvCreateImageHeader(cvSize(ROI_BOX_W2, ROI_BOX_H2),
BITS_PER_PIXEL, NUM_CHANNELS);
cvNamedWindow(DISPLAY2, CV_WINDOW_AUTOSIZE);
#endif
// initialize the tracking window (i.e. blob and ROI positions)
memset(&cur[0], 0, sizeof(TrackingWindow));
set_initial_positions(&cur[0]);

memset(&cur[1], 0, sizeof(TrackingWindow));
set_initial_positions2(&cur[1]);

memset(&cur[2], 0, sizeof(TrackingWindow));
set_initial_positions3(&cur[2]);

// initialize the camera
rc = init_cam(&fg, MEMSIZE(cur[0].roi_w, cur[0].roi_h), NUM_BUFFERS, CAMLINK);
if(rc != FG_OK) {
printf("init: %s\n", Fg_getLastErrorDescription(fg));
Fg_FreeGrabber(fg);
//return rc;
}
// start acquiring images (this function also writes any buffered ROIs to the camera)
rc = acquire_imgs(fg, (int *) &seq, SEQ_LEN);
if(rc != FG_OK) {
printf("init: %s\n", Fg_getLastErrorDescription(fg));
Fg_FreeGrabber(fg);
//return rc;
}

// initialize parameters
//img_nr = 1;
int initnum;

QueryPerformanceFrequency(&timing.freq);
}

// de-allocate memory
void memclear(void) {
// free camera resources
rc = deinit_cam(fg);
if(rc != FG_OK) {
printf("deinit: %s\n", Fg_getLastErrorDescription(fg));
//return rc;
}
}
// get the images and process them
void takePicture(double *coords)
{
int i;
static int img_nr = 1;

// start a timer
QueryPerformanceCounter(&timing.grab_start);
// get number of last image acquired
img_nr = Fg_getLastPicNumberBlocking(fg, 1, PORT_A, TIMEOUT);
// stop timer
QueryPerformanceCounter(&timing.grab_stop);

// record image number
coords[12] = img_nr;
// record image number modulo 3
coords[13] = img_nr%3;
// record time it took to acquire last image
coords[14] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;

QueryPerformanceCounter(&timing.grab_start);
// camera has taken picture of the real ball
if (img_nr%3 == 1) {
cur[0].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
img_nr = Fg_getLastPicNumberBlocking(fg, img_nr+1, PORT_A, TIMEOUT);
cur[1].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
img_nr = Fg_getLastPicNumberBlocking(fg, img_nr+1, PORT_A, TIMEOUT);
cur[2].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
}
// camera has taken picture of the reflected ball
else if (img_nr%3 == 2) {
cur[1].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
cur[0].img = (unsigned char *) Fg_getImagePtr(fg, img_nr-1, PORT_A);
img_nr = Fg_getLastPicNumberBlocking(fg, img_nr+1, PORT_A, TIMEOUT);
cur[2].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
}
// camera has taken picture of the bar
else {
cur[2].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
cur[1].img = (unsigned char *) Fg_getImagePtr(fg, img_nr-1, PORT_A);
cur[0].img = (unsigned char *) Fg_getImagePtr(fg, img_nr-2, PORT_A);
}
QueryPerformanceCounter(&timing.grab_stop);
// record time to get images
coords[15] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;

QueryPerformanceCounter(&timing.grab_start);
for (index=0;index<3;index++) {
// process image
threshold(&cur[index], THRESHOLD);
erode(&cur[index]);
// calculate centroid
centroid(&cur[index]);
// Transform coordinates from camera frame to realworld frame
if (index == 1) {
trans_coords2(&cur[index]);
}
else {
trans_coords(&cur[index]);
}

// create timestamp
timeMs = img_nr;
Fg_getParameter(fg, FG_TIMESTAMP,
&timeMs, PORT_A);
//printf("\n%d\n", time);
// updata position
position(&cur[index]);

// at this point position(...) has updated the ROI, but it only stores
// the updated values internal to the code. The next step is to flushq
// the ROI to the camera (see position(...) documentation).

// write ROI position to camera to be updated on frame "img_nr"
write_roi(fg, cur[index].roi, img_nr + 6, !DO_INIT);

// show image on screen
if (DISPLAY_TRACKING) {
display_tracking(&cur[index], cvDisplay[index]);
}

// record data for reflected ball image
if (index%3 == 1) {
coords[5] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
coords[3] = (double) cur[1].xc;
coords[4] = (double) cur[1].yc;
//printf("%f,%f,%f \n",coords[3],coords[4],coords[5]);
coords[10] = img_nr;
}
// record data for bar image
else if (index%3 == 2) {
coords[8] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
coords[6] = (double) cur[2].xc;
coords[7] = (double) cur[2].yc;
//printf("%f,%f,%f \n",coords[6],coords[7],coords[8]);
coords[11] = img_nr;
}
// record data for real ball image
else {
coords[2] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
coords[0] = (double) cur[0].xc;
coords[1] = (double) cur[0].yc;
//printf("%f,%f \n",cur[0].xc,cur[0].yc);
coords[9] = img_nr;
}
}
QueryPerformanceCounter(&timing.grab_stop);
// record time to process images
coords[16] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;

// old method of executing this code, wherein each time the MEX-file is accessed,
// first one picture is taken and processed, then the next, and then the next. That
// method could be sped up with the technique that is employed now. I left the code
// in comment below just in case it is ever needed again.
/*
for (i=0;i<3;i++) {
QueryPerformanceCounter(&timing.grab_start);
img_nr = Fg_getLastPicNumberBlocking(fg, img_nr, PORT_A, TIMEOUT);
QueryPerformanceCounter(&timing.grab_stop);

// Obtain index for ROI based on image number
if (img_nr%3 == 1) {
index = 0;
}
else if (img_nr%3 == 2) {
index = 1;
}
else {
index = 2;
}
cur[index].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);

// make sure that camera returned a valid image
if (cur[index].img == NULL) {
// typically this state only occurs if an invalid ROI has been programmed
// into the camera (e.g. roi_w == 4).
printf("img is null: %d\n", img_nr);
//system("PAUSE");
//break;
}
// process image
threshold(&cur[index], THRESHOLD);
erode(&cur[index]);
// calculate centroid
centroid(&cur[index]);
// Transform coordinates from camera frame to realworld frame
if (index == 1) {
trans_coords2(&cur[index]);
}
else {
trans_coords(&cur[index]);
}

// create timestamp
timeMs = img_nr;
Fg_getParameter(fg, FG_TIMESTAMP,
&timeMs, PORT_A);
//printf("\n%d\n", time);
// updata position
position(&cur[index]);

// at this point position(...) has updated the ROI, but it only stores
// the updated values internal to the code. The next step is to flushq
// the ROI to the camera (see position(...) documentation).

// write ROI position to camera to be updated on frame "img_nr"
write_roi(fg, cur[index].roi, img_nr + 6, !DO_INIT);

// show image on screen
if (DISPLAY_TRACKING) {
display_tracking(&cur[index], cvDisplay[index]);
}

// increment to the next desired frame. This has to be at least
// +2, because the camera's ROI will not be active until the second
// frame (see Silicon Software FastConfig doc)

//img_nr += NEXT_IMAGE;

//QueryPerformanceCounter(&timing.grab_stop);

if (img_nr%3 == 2) {
coords[5] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
coords[3] = (double) cur[1].xc;
coords[4] = (double) cur[1].yc;
//printf("%f,%f,%f \n",coords[3],coords[4],coords[5]);
coords[10] = img_nr;
}
else if (img_nr%3 == 0) {
coords[8] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
coords[6] = (double) cur[2].xc;
coords[7] = (double) cur[2].yc;
//printf("%f,%f,%f \n",coords[6],coords[7],coords[8]);
coords[11] = img_nr;
}
else {
coords[2] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
coords[0] = (double) cur[0].xc;
coords[1] = (double) cur[0].yc;
//printf("%f,%f \n",cur[0].xc,cur[0].yc);
coords[9] = img_nr;
}
img_nr += NEXT_IMAGE;
}
*/
}

// MEX function
void mexFunction( int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[])
{
int select; /* input scalar */
double *outMatrix; /* output matrix */
/* get the value of the selector */
select = mxGetScalar(prhs[0]);

/* create the output matrix */
plhs[0] = mxCreateDoubleMatrix(1,17,mxREAL);

/* get a pointer to the real data in the output matrix */
outMatrix = mxGetPr(plhs[0]);

// choose which function to execute based on input from MATLAB
if (select == 0) {
initialization();
}
else if (select == 1) {
takePicture(outMatrix);
}
else {
memclear();
}
}
}
</nowiki>
</nowiki>

Latest revision as of 16:01, 11 September 2009

Stripping Down Windows

To make the new computer that runs the control system run as efficiently as possible, all extraneous functionalities were turned off. There is not anti-virus software, no firewall, no https for the internet, and so on. Only the bare minimum is left. Below is a list of the remaining functions and what they do. Another thing to do to make MATLAB run faster is to set it to go to the Task Manager, go to Processes, right-click on MATLAB.exe and set it to Realtime priority.

Explorer.exe

This is the user shell, which we see as the familiar taskbar, desktop, and other user interface features. This process isn't as vital to the running of Windows as you might expect, and can be stopped (and restarted) from Task Manager, usually with no negative side effects on other applications.

nvsvc32.exe

Part of the NVIDIA graphics card drivers (Detonator). It should be left running on any system using Nvidia graphics hardware to ensure proper function.

MATLAB.exe

MATLAB

svchost.exe

an integral part of Windows OS. It cannot be stopped or restarted manually. This process manages 32-bit DLLs and other services. At startup, Svchost.exe checks the services portion of the registry and constructs a list of services that it needs to load. Under normal conditions, multiple instances of Svchost.exe will be running simultaneously. Each Svchost.exe session can contain a grouping of services, so that many services can be run depending on how and where Svchost.exe is started. This allows for better control and debugging.

lsass.exe

the Local Security Authentication Server. It verifies the validity of user logons to your PC or server. Lsass generates the process responsible for authenticating users for the Winlogon service. This is performed by using authentication packages such as the default, Msgina.dll. If authentication is successful, Lsass generates the user's access token, which is used to launch the initial shell. Other processes that the user initiates then inherit this token.

services.exe

This is the Services Control Manager, which is responsible for running, ending, and interacting with system services. Use this program to start services, stop them, or change their default from automatic to manual startup.

winlogon.exe

runs in the background. Winlogon is a part of the Windows Login subsystem, and is necessary for user authorization and Windows XP activation checks.

csrss.exe

This is the user-mode portion of the Win32 subsystem; Win32.sys is the kernel-mode portion. Csrss stands for Client/Server Run-Time Subsystem, and is an essential subsystem that must be running at all times. Csrss is responsible for console windows, creating and/or deleting threads, and implementing some portions of the 16-bit virtual MS-DOS environment.

smss.exe

This is the session manager subsystem, which is responsible for starting the user session. This process is initiated by the main system thread and is responsible for various activities, including launching the Winlogon and Win32 (Csrss.exe) processes, and setting system variables. After it has launched these processes, it waits for either Winlogon or Csrss to end. If this happens normally, the system shuts down; if it happens unexpectedly, Smss.exe causes the system to stop responding (hang).

ctfmon.exe

When you run a Microsoft Office XP program, the file Ctfmon.exe (Ctfmon) runs in the background, even after you quit all Office programs. Ctfmon.exe monitors active windows and provides text input service support for speech recognition, handwriting recognition, keyboard translation, and other alternate user input forms.

rundll32.exe

This program is part of Windows, and is used to run program code in DLL files as if they were within the actual program.

RTHDCPL.EXE

a process belonging to the Realtek HD Audio Control Panel and is bundled alongside Realtek sound cards and audio hardware. This program is a non-essential process, but should not be terminated unless suspected to be causing problems.

ipoint.exe

a process installed alongside a Microsoft IntelliMouse and provides additional configuration options for these devices. "This program is a non-essential process, but should not be terminated unless suspected to be causing problems.

System

a process which shows up on the tasks on mainly Windows XP, Windows 2003 server and later version of Windows. This is a default system counter and cannot be removed.


Shared Memory

One of the methods explored to make the system run as quickly as possible was to have MATLAB and the camera running on separate cores of the computer, so both could run in parallel. This would require for them to communicate through shared memory. At the bottom of this page is a .cpp program that communicates through shared memory. We ultimately did not take this approach because Windows appears to be quick enough for now. Eventually, a real-time operating system such as Linux RTAI would be preferred, but for the time being, Windows suffices. I will therefore not explain further how the shared memory option works. However, if it is ever needed, everything to communicate through shared memory is in that file.


Test of Sample Rates

Overview

To see if using Windows instead of a real-time operating system would be a viable option, we had to test how fast the sampling rate could be set to without losing samples. We tried two methods: the first was to output data on one computer and collect it on the same computer, and the second was to output data on one computer and collect it on another computer.

Single Computer Tests

Pulses
To run these tests, we used Measurement Computing Cards (mcc). Both were installed in the same computer. The MATLAB code that is at the end of this document was then run (testInputOutput.m). It creates an output wave that is a wave of alternating pulses. These were output at a predetermined rate. The input card kept on taking input all the time. Then, the duration of the input pulses was measured to see how long each pulse actually was as opposed to how long we wanted it to be. Plots of this were made, along with the standard deviation and the extra duration of each pulse. Using this method, we were able to see how fast we could feasibly run the alternate pulses without losing accuracy. Figure 1 shows that this test started to break down around 2000 Hz.

Figure 1: Number of pulses with given duration.

Two Computers

Pulses
The next step was to output data on one computer and to input data on another. For output, we again used the mcc card. For input, however, we used a National Instruments (ni) card. Two programs were run for this test. The program run from the output computer was testOutput.m, and the one run on the input computer was testInputCard.m. With this simple modification to the setup, the test still ran fine at 10000 Hz, as can be seen in Figure 2.

Figure 2: Number of pulses with given duration.

Single Computer Again

Sine Wave
Following the tests with pulses, we decided to try to send a sine wave instead of a pulse, and to see at what output sample rate the frequency of the wave started to become inaccurate. This test is more practical, since in reality we would be sending sine waves and not pulses, and a little error in the output wave is acceptable in our applications. We used the same single computer setup as before, and ran the code inputOutputSineWave.m. A result of this test can be seen in Figure 3.

Figure 3: Frequency of sine wave with requested frequency of 50 Hz.

Sine Wave Sweep
Finally, we decided to try a sweep of sine wave frequencies to determine exactly where the input frequency breaks down. The code that was run is called sweepOfSampleRatesSineWave.m. The results of this can be seen in Figure 4. This breakdown occurred at 8100 Hz.

Figure 4: Sweep of requested sample rates.


Integration of Systems

To begin

Make sure the National Instruments input and output cards are hooked up and set up with the new computer. On line 39 of the program “integrationTestPutSample.m”, make sure the right device number is chosen. As the program runs now, only the bottom two speakers are controlled, and the left and right speakers don’t move. Make sure the camera is calibrated properly. Run the .m file, and the ball should be bounced to an average height of 20 mm. This is a test of the closed feedback loop from the camera.

Contents of programs

The program consists of two separate programs. There is the MATLAB .m file, “integrationTestPutSample.m”, and the MEX-file, “skeleton.cpp”. The analysis of the data collected is done in MATLAB, where it can be seen in the beginning that a lot of matrices are set up to hold data. Then, the MATLAB program calls the MEX-file, which returns a lot of data, and that data is analyzed in MATLAB. The MEX-file itself takes the pictures and does image processing, calculating the centroid of each picture of the bouncing ball. All the functions in both the .m file and the .cpp file are documented within the programs.

Overview of operation of control system

First, the camera and the framegrabber are initialized by allocating space in memory for the images that will be taken. Then, the camera starts taking pictures at a pre-specified rate (FRAME_TIME in the constants.h file). The three most recent pictures (real ball, reflected ball, and bar) are then taken from the image buffer and the coordinates of each centroid are calculated with some image processing algorithms. Then, these coordinates are used as input to another function in MATLAB to calculate x, y, and z coordinates for the ball and x and z coordinates for the bar. After that, the program checks if the ball is below 14.5 mm from the bar. If it is, half a period of sine wave is input into the speakers, and the ball is bounced back up. If the previous bounce of the ball was above 21 mm, the amplitude of the sine wave is reduced a little. If the previous bounce was below 19 mm, the amplitude of the sine wave is increased a little. This keeps the ball bouncing to approximately 20 mm. This loop then runs for as long as is specified, and afterwards the space allocated for the images is de-allocated.

Timing

The timing of the system is detailed on the timing diagrams (Fig 5 and 6). The idea, which is not fully implemented yet, is to have there be two pictures already taken when the MATLAB program calls the MEX-file, so that the program waits for only one more picture to be taken and then grabs all three and processes them all. To implement this, the frame time has to be just a little shorter than half of the total processing time, including the MEX-file processing and the MATLAB processing. With a frame time of 500 microseconds, the system keeps up fine and can take pictures at 2000 frames per second. However, tweaking the frame time and exposure time to fit more neatly with processing time can make the system more efficient and perhaps even put the rate to over 2000 Hz, depending on how fast the processing can be done.

Figure 5: Timing Diagram.
Figure 6: Blowup of Timing Diagram.

Next Steps

In the future, more things can be done to further speed up the system. First of all, using separate cores for the camera and processing may speed up the system as the two tasks would run in parallel. This would require shared memory. Another step that can be taken is to implement all the MATLAB computations in C. This would help because C is quicker than MATLAB and because MATLAB wouldn't have to access the MEX-file every time it wants to take a picture. Also, using a real-time operating system like Linux RTAI would also speed up the process. Stripping down Windows makes it close to real-time, but in reality it is not real-time.

Code

Shared Memory

 
#include <windows.h>
#include <stdio.h>
#include <conio.h>
#include <tchar.h> 

#define BUF_SIZE 256
TCHAR szName[]=TEXT("Global\\MyFileMappingObject");
//TCHAR szMsg[]=TEXT("What's up (from the first process)?");
int szMsg;

int _tmain()
{
   HANDLE hMapFile;
   LPCTSTR pBuf;
   int ch,image;
   int coordinates[3];

   hMapFile = CreateFileMapping(
                 INVALID_HANDLE_VALUE,    // use paging file
                 NULL,                    // default security 
                 PAGE_READWRITE,          // read/write access
                 0,                       // max. object size 
                 BUF_SIZE,                // buffer size  
                 szName);                 // name of mapping object
 
   if (hMapFile == NULL) 
   { 
      _tprintf(TEXT("Could not create file mapping object (%d).\n"), 
             GetLastError());
      return 1;
   }
   pBuf = (LPTSTR) MapViewOfFile(hMapFile,   // handle to map object
                        FILE_MAP_ALL_ACCESS, // read/write permission
                        0,                   
                        0,                   
                        BUF_SIZE);           
 
   if (pBuf == NULL) 
   { 
      _tprintf(TEXT("Could not map view of file (%d).\n"), 
             GetLastError()); 

	  CloseHandle(hMapFile);

      return 1;
   }

   for (szMsg=0;szMsg<5;szMsg++) {
	   image = szMsg*2;
	   coordinates[0] = image * 2;
       coordinates[1] = image * 3;
       coordinates[2] = image * 4;

	   CopyMemory((PVOID)pBuf, coordinates, (3*sizeof(int)));

	   _cputs( "Type 'Y' to increment counter: " );
	   do
	   {
		  ch = _getch();
		  ch = toupper( ch );
	   } while( ch != 'Y' );

	   _putch( ch );
	   _putch( '\r' );    // Carriage return
	   _putch( '\n' );    // Line feed  
   }

   UnmapViewOfFile(pBuf);

   CloseHandle(hMapFile);

   return 0;
}



#include <windows.h>
#include <stdio.h>
#include <conio.h>
#include <tchar.h>
#pragma comment(lib, "user32.lib")

#define BUF_SIZE 256
TCHAR szName[]=TEXT("Global\\MyFileMappingObject");

int _tmain()
{
   HANDLE hMapFile;
   LPCTSTR pBuf;
   int i;
   double coordinates[3];
   int temp;
   const char *tempChar;

   hMapFile = OpenFileMapping(
                   FILE_MAP_ALL_ACCESS,   // read/write access
                   FALSE,                 // do not inherit the name
                   szName);               // name of mapping object 
 
   if (hMapFile == NULL) 
   { 
      _tprintf(TEXT("Could not open file mapping object (%d).\n"), 
             GetLastError());
      return 1;
   } 

   pBuf = (LPTSTR) MapViewOfFile(hMapFile, // handle to map object
               FILE_MAP_ALL_ACCESS,  // read/write permission
               0,                    
               0,                    
               BUF_SIZE);                   
 
   if (pBuf == NULL) 
   { 
      _tprintf(TEXT("Could not map view of file (%d).\n"), 
             GetLastError()); 

	  CloseHandle(hMapFile);

      return 1;
   }

   tempChar = (const char *) pBuf;
   temp = atoi(tempChar);
   do {
	for (i=0; i<3; i++){
		*(coordinates+i) = (double) (atoi((const char *) (&(*(pBuf+i)))));
	}
   } while (1);

   UnmapViewOfFile(pBuf);

   CloseHandle(hMapFile);
 
   return 0;
}

testInputOutput.m

clear all
close all
% set a desired sample rate of output
sampRate = 5000;
dt = 1/sampRate;
amp = 1;
% set input card's sample rate
sampRateIn = 50000;
% amount of time to acquire data
timeIn = 10;
trigger = timeIn*sampRateIn;

% creat input and output objects
AI = analoginput('mcc',0);
AO = analogoutput('mcc',1);

% add channels
addchannel(AI,[0:5],[1:6]);
addchannel(AO,[0:5],[1:6]);

% set up cards
set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)
set(AO,'SampleRate',ceil(1/500))

time = 1/sampRateIn:1/sampRateIn:timeIn;
t = 0:dt:timeIn;

% create an output wave that is just an alternating pulse
outputwave = zeros(length(t),1);
for jj = 1:floor(length(t)/2)
    outputwave(2*jj,1) = amp;
end
outputwave(:,2) = outputwave;
outputwave(:,[2 3 4 5 6]) = 0;

temp = rand(10);

% start acquisition
start(AI)
tic
a = 0;
% output data
for ii = 1:length(outputwave)
    while(toc<(dt*ii))
    end
    putsample(AO,outputwave(ii,:));
    %z = sampleMexFile(ii,ii,ii);
    %fft(outputwave);
    %fprintf('pause: %f\n',dt-time);
    %data(ii,:) = getsample(AI);
end

% collect data
data = getdata(AI);
stop(AI);
delete(AI)
clear AI

% get meaningful data from the channel that matters
meaningfulData = data(:,1);
plot(time,meaningfulData);

freqData = zeros(trigger,1);
counter = 0;
pulseCounter = 1;
% count number of pulses that have a specific duration
for ii = 2:trigger
    if (abs(meaningfulData(ii) - meaningfulData(ii-1)) < .05)
        counter = counter + 1;
    elseif ((counter ~= 0) && (ii-counter > 3))
        freqData(counter) = freqData(counter) + 1;
        pulseDuration(pulseCounter) = counter/sampRateIn;
        counter = 0;
        pulseCounter = pulseCounter + 1;
    elseif (ii-counter == 3)
        counter = 0;
    end
end

average = 1/sampRate;
figure
% create a graph of pulse durations
stem(time(1:2*average*sampRateIn),freqData(1:2*average*sampRateIn));
title(['Number of Pulses with Given Duration, Recorded for ',num2str(timeIn),' Seconds (',num2str(sampRate),' Hz)']);
xlabel('Pulse Duration (sec)');
ylabel('Number of Pulses');

averageDuration = 0;
for jj = 1:trigger
    if (freqData(jj) ~= 0)
        fprintf('%u pulses had duration of: %f \n',freqData(jj),jj/sampRateIn);
        averageDuration = averageDuration + (freqData(jj)*jj/sampRateIn);
    end
end
fprintf('\n');
averageDuration = averageDuration/sum(freqData);
fprintf('Average duration of pulses: %f \n\n',averageDuration);

standardDev = 0;
% find the standard deviation
for jj = 1:trigger
    if (freqData(jj) ~= 0)
        for kk = 1:freqData(jj)
            standardDev = standardDev + (averageDuration - (jj/sampRateIn))^2;
        end
    end
end
standardDev = sqrt(standardDev/(sum(freqData) - 1));
fprintf('Standard deviation of duration of pulses: %f \n\n\n',standardDev);

pulseDuration = pulseDuration - mode(pulseDuration);
figure
% plot how much longer or shorter pulses were than what was requested
stem(pulseDuration/dt);
title('Pulse Duration vs. Time')
xlabel('Time (sec)')
ylabel(['Extra length of pulse in terms of dt (',num2str(dt),' seconds)']);

testOutput.m

clear all
close all
sampRate = 5000;
dt = 1/sampRate;
freq = 30;
timeIn = 30;
amp = 1;

AO = analogoutput('mcc',1);
addchannel(AO,[0:5],[1:6]);
set(AO,'SampleRate',ceil(1/500))

t = 0:dt:timeIn;

outputwave = zeros(length(t),1);
for jj = 1:floor(length(t)/2)
    outputwave(2*jj,1) = amp;
end
outputwave(:,2) = outputwave;
outputwave(:,[2 3 4 5 6]) = 0;

tic
for ii = 1:length(outputwave)
    while(toc<(dt*ii))
    end
    putsample(AO,outputwave(ii,:));
    %z = sampleMexFile(ii,ii,ii);
    %fft(outputwave);
    %fprintf('pause: %f\n',dt-time);
    %data(ii,:) = getsample(AI);
end

testInputCard.m

clear all
close all
dt = 1/500;
freq = 30;
sampRateIn = 50000;
trigger = 100000;

time = 1/sampRateIn:1/sampRateIn:trigger/sampRateIn;

AI = analoginput('mcc',0);
addchannel(AI,[0:5],[1:6]);

set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)

start(AI)
data = getdata(AI);
meaningfulData = data(:,1);
plot(time,meaningfulData);

freqData = zeros(trigger,1);
counter = 0;
for ii = 2:trigger
    if (abs(meaningfulData(ii) - meaningfulData(ii-1)) < .05)
        counter = counter + 1;
    elseif ((counter ~= 0) && (ii-counter > 3))
        freqData(counter) = freqData(counter) + 1;
        counter = 0;
    elseif (ii-counter == 3)
        counter = 0;
    end
end

figure
stem(time,freqData);

for jj = 1:trigger
    if (freqData(jj) ~= 0)
        fprintf('%u pulses had duration of: %f \n',freqData(jj),jj/sampRateIn);
    end
end

inputOutputSineWave.m

clear all
close all
sampRate = 200;
dt = 1/sampRate;
freq = 50;
amp = 1;
sampRateIn = 50000;
timeIn = 10;
trigger = timeIn*sampRateIn;

AI = analoginput('mcc',0);
AO = analogoutput('mcc',1);

addchannel(AI,[0:5],[1:6]);
addchannel(AO,[0:5],[1:6]);

set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)
set(AO,'SampleRate',ceil(1/500))

time = 1/sampRateIn:1/sampRateIn:timeIn;
t = dt:dt:timeIn;

outputwave = amp*sin(2*pi*freq*t);
outputwave = outputwave';
outputwave(:,2) = amp*sin(2*pi*freq*t);
outputwave(:,[3 4 5 6]) = 0;

start(AI)
tic
a = 0;
for ii = 1:length(outputwave)
    while(toc<(dt*ii))
    end
    putsample(AO,outputwave(ii,:));
    z = sampleMexFile(ii,ii,ii);
end

data = getdata(AI);
stop(AI);
delete(AI)
clear AI

meaningfulData = data(:,1);
plot(time,meaningfulData);

[YfreqDomain,frequencyRange] = positiveFFT(meaningfulData,sampRateIn);
positiveFFT = figure;
stem(frequencyRange,abs(YfreqDomain));
xlabel('Freq (Hz)')
ylabel('Amplitude')
title('FFT')
grid
axis([0,2*freq,0,amp])

NFFT = 2^nextpow2(length(meaningfulData)); % Next power of 2 from length of y
Y = fft(meaningfulData,NFFT)/length(meaningfulData);
f = sampRateIn/2*linspace(0,1,NFFT/2+1);
figure
plot(f,2*abs(Y(1:NFFT/2+1)))
title(['Single-Sided Amplitude Spectrum of y(t) (',num2str(freq),' Hz) @ ',num2str(sampRate),' Hz'])
xlabel('Frequency (Hz)')
ylabel('|Y(f)|')
axis([0,2*freq,0,amp])

[a,b] = max(Y(1:NFFT/2+1));
actualFreq = f(b);
fprintf(['\nRequested frequency: ',num2str(freq), ' Hz\n']);
fprintf(['Actual frequency: ',num2str(actualFreq), ' Hz\n']);

sweepOfSampleRatesSineWave

clear all
close all

freq = 50;
amp = 1;
sampRateIn = 50000;
timeIn = 10;
trigger = timeIn*sampRateIn;

AI = analoginput('mcc',0);
AO = analogoutput('mcc',1);

addchannel(AI,[0:5],[1:6]);
addchannel(AO,[0:5],[1:6]);

set(AI,'SampleRate',sampRateIn)
set(AI,'SamplesPerTrigger',trigger)
set(AO,'SampleRate',ceil(1/500))

time = 1/sampRateIn:1/sampRateIn:timeIn;

sweep = zeros(100,3);
for sr = 500:100:10000
    sampRate = sr;
    dt = 1/sampRate;
    
    t = 0:dt:timeIn;

    outputwave = amp*sin(2*pi*freq*t);
    outputwave = outputwave';
    outputwave(:,2) = amp*sin(2*pi*freq*t);
    outputwave(:,[3 4 5 6]) = 0;

    start(AI)
    tic
    for ii = 1:length(outputwave)
        while(toc<(dt*ii))
        end
        putsample(AO,outputwave(ii,:));
        %fprintf('pause: %f\n',dt-time);
        %data(ii,:) = getsample(AI);
    end

    data = getdata(AI);
    stop(AI);

    meaningfulData = data(:,1);
    
    NFFT = 2^nextpow2(length(meaningfulData)); % Next power of 2 from length of y
    Y = fft(meaningfulData,NFFT)/length(meaningfulData);
    f = sampRateIn/2*linspace(0,1,NFFT/2+1);
%     figure
%     plot(f,2*abs(Y(1:NFFT/2+1)))
%     title(['Single-Sided Amplitude Spectrum of y(t) (',num2str(freq),' Hz) @ ',num2str(sampRate),' Hz'])
%     xlabel('Frequency (Hz)')
%     ylabel('|Y(f)|')
%     axis([0,2*freq,0,amp])

    [a,b] = max(Y(1:NFFT/2+1));
    actualFreq = f(b);
    
    sweep(sr/100,1) = sr;
    sweep(sr/100,2) = actualFreq;
end

figure
plot(sweep(:,1), sweep(:,2));

integrationTestPutSample.m

% This program is a simple control system to test the functionality of the
% camera and actuator closed-loop feedback system.  The camera takes
% pictures at a predetermined rate (set in the MEX-file).  This program
% accesses the MEX-file and takes the three most recent pictures from the
% image buffer.  The coordinates of the centroid of each image are then
% calculated.  These coordinates are passed back into this program, where
% the x, y, and z coordinates of the ball are computed and the x and z
% coordinates of the bar are computed.  After that, the program checks if
% the ball is below 14.5 mm from the bar.  If it is, half a period of a
% sine wave is input into the speakers, and the ball is bounced back up.
% If the previous bounce of the ball was above 21 mm, the amplitude of the
% sine wave is reduced a little.  If the pervious bounce was below 19 mm,
% the amplitude of the sine wave is increased a little.  This keeps the
% ball bouncing to approximately 20 mm.  This loop then runs for as long as
% is specified, and afterwards the space allocated for the images is
% de-allocated.

clear all
close all

% load calibration constants
calib = '8-17-09 Calibration Constants';
load(calib);

% compile the MEX-file
mex -L'C:\PROGRA~1\SiliconSoftware3.2\lib\visualc' -L'C:\Program Files\OpenCV\lib' -ldisplay_lib -lclserme3 -lclsersisome3 -lfastconfig -lfglib3.1 -lfglib3 -liolib -lmenable3 -lhighgui -lcv -lcvaux -lcvcam -lcvhaartraining -lcxcore -lcxts -lml skeleton.cpp cam.cpp imgproc.cpp roi.cpp tracking.cpp utils.cpp
% initialize camera and framegrabber
skeleton(0);

% set the sample rate of the data input into the speakers
sampRate = 2000;
dt = 1/sampRate;
% set the frequency of the sine wave
freq = 30;
amp = 2;
timeOnePeriod = 1/freq;

% create an analog output object
AO = analogoutput('nidaq','Dev3');

% add 2 channels for the two bottom speakers
addchannel(AO,2:3);

% set a sample rate for the output (only matters is the command "putdata"
% is used).
set(AO,'SampleRate',sampRate);

t = 0:dt:timeOnePeriod/2;

% create output wave
outputwave = amp*sin(2*pi*freq*t);
outputwave = outputwave';
outputwave(:,2) = amp*sin(2*pi*freq*t);

% set the length of the loop
lenLoop = 10000;

% initialize vectors to store useful data
height_ball = zeros(1,lenLoop);
height_bar = zeros(1,lenLoop);
proportional = zeros(1,lenLoop);
multArray = zeros(1,lenLoop);
timeArray = zeros(2,lenLoop);
eventTimer = zeros(1,3*lenLoop);
imageNumber = zeros(1,3*lenLoop);
times = zeros(5,lenLoop);

% initialize useful variables
previousHeight = 0;
goingDown = 0;
time_ball(1) = 0;
multiplier = 2;
P = 13.8;
ii = 1;

% start actual control system
while ii<(lenLoop+1)
    % access the MEX-file and store results in variable "temp"
    temp = skeleton(1);
    % use proper entries from "temp" to create inputs for the
    % calc_coords3ROI function
    XZ = [1 temp(3) temp(1) temp(2)];
    YZ = [1 temp(6) temp(4) temp(5)];
    bar_tracking = [1 temp(9) temp(7) temp(8)];
    
    %eventTimer((3*ii)-2:(3*ii)) = [temp(3) temp(6) temp(9)];
    %imageNumber((3*ii)-2:(3*ii)) = [temp(10) temp(11) temp(12)];
    
    % store the image number, image number modulo 3, time to get first
    % image number, time to get rest of images, and time to process images
    times(:,ii) = [temp(13); temp(14); temp(15); temp(16); temp(17)];
    % calculate coordinates
    [XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
    % check if bar has to bounce
    if XYZ_BALL(5) > 13.9 && XYZ_BALL(5) < 14.5
        % check if ball bounced too high
        if P > 21
            % adjust amplitude of output wave
            multiplier = multiplier - .1;
        % check if ball bounced too low
        elseif P < 19 && multiplier < 4
            % adjust amplitude of output wave
            multiplier = multiplier + .1;
        end
        tic
        % load output wave into speakers
        for kk = 1:length(outputwave)
            while(toc<(dt*kk))
            end
            temp2 = toc;
            putsample(AO,multiplier*outputwave(kk,:));
            temp = skeleton(1);
            XZ = [1 temp(3) temp(1) temp(2)];
            YZ = [1 temp(6) temp(4) temp(5)];
            bar_tracking = [1 temp(9) temp(7) temp(8)];
            %eventTimer((3*ii)-2:(3*ii)) = [temp(3) temp(6) temp(9)];
            %imageNumber((3*ii)-2:(3*ii)) = [temp(10) temp(11) temp(12)];
            times(:,ii) = [temp(13); temp(14); temp(15); temp(16); temp(17)];
            [XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
            timeArray(1,ii) = toc - temp2;
            height_bar(ii) = XZ_BAR(4);
            height_ball(ii) = XYZ_BALL(5);
            ii = ii + 1;
            if ii>(lenLoop-1)
                break
            end
        end
        timeArray(2,ii) = toc;
        multArray(ii) = multiplier;
    % if ball settles on lens, wait one second and then bounce it back up
    elseif XYZ_BALL(5) < 13.9
        tic
        while XYZ_BALL(5) < 13.9
            temp = skeleton(1);
            XZ = [1 temp(3) temp(1) temp(2)];
            YZ = [1 temp(6) temp(4) temp(5)];
            bar_tracking = [1 temp(9) temp(7) temp(8)];
            [XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
            if toc > 1
                tic
                for kk = 1:length(outputwave)
                    while(toc<(dt*kk))
                    end
                    putsample(AO,4*outputwave(kk,:));
                    temp = skeleton(1);
                    XZ = [1 temp(3) temp(1) temp(2)];
                    YZ = [1 temp(6) temp(4) temp(5)];
                    bar_tracking = [1 temp(9) temp(7) temp(8)];
                    [XYZ_BALL, XZ_BAR] = calc_coords3ROI(XZ,YZ,bar_tracking);
                    height_bar(ii) = XZ_BAR(4);
                    height_ball(ii) = XYZ_BALL(5);
                    ii = ii + 1;
                end
            end
        end
    end
    % record the height of the previous bounce
    if XYZ_BALL(5) < previousHeight && goingDown == 0
        goingDown = 1;
        P = previousHeight;
        proportional(ii) = P;
    elseif XYZ_BALL(5) > previousHeight && goingDown == 1
        goingDown = 0;
    end
    previousHeight = XYZ_BALL(5);
    height_ball(ii) = XYZ_BALL(5);
    height_bar(ii) = XZ_BAR(4);
    ii = ii + 1;
end

% de-allocate memory
skeleton(2);

% make plots of data
figure
plot(height_ball);
title('Height of Ball');
figure
stem(proportional);
title('Max Height of Each Bounce');
figure
stem(multArray);
title('Multiplier');
figure
plot(height_bar);
title('Height of Bar');
% figure
% plot(timeArray(1,:));
% figure
% stem(imageNumber,eventTimer);
% title('Time for Event');

% find average height of bounces
j = 1;
for i = 1:length(proportional) 
    if proportional(i) ~= 0 
        temporary(j) = proportional(i); 
        j = j+1; 
    end
end
mean(temporary)

% j = 1;
% for i = 1:length(eventTimer)/3
%     temporary3(j) = mean(eventTimer((3*i)-2:(3*i)));
%     j = j+1;
% end
% figure
% stem(temporary3);
% mean(temporary3)

skeleton.cpp

/**
* @file skeleton.cpp displays code for a simple one ROI tracker
*
* skeleton.cpp contains the necessary components to start and modify the vision system for
* application-specific tracking/image processing tasks.  The code is comprised of three
* functions: set_initial_positions(...), display_tracking(...), and main().
*
* set_initial_positions(...) shows one possible initialization strategy for the camera's
* ROI.  This implementation simply takes the known initial position of the object to track
* (the blob) and centers the camera's ROI bounding box around that center.
*
* display_tracking(...) is a sample application of interest for showing (processed) camera
* frames.  A function like this also provides visual feedback of what is going on 
* internally in the system and is an invaluable debugging tool (see display_run.cpp for
* a more complicated example).
*
* Finally, main() is the starting point of the program.  Its role is to initialize the
* camera and run the logic necessary for tracking objects.
*
* Most, if not all, applications will follow this recipe of initialization routines,
* application-specific routines, and finally a main program that sits in a loop acquiring
* the next image to process.  A few common setup and helper functions can be found in 
* utils.cpp.
*/

#include "fcdynamic.h"
#include "constants.h"
#include "mex.h"

/** Grabs an image from the camera and displays the image on screen
*
*  The purpose of this program is to show how to get the camera up and running.
*  Modifications can be made by modifying the while(...) loop with different image
*  processing and tracking logic.
*/

// important variables used in most applications
int rc;
Fg_Struct *fg = NULL;
TrackingWindow cur[NUM_ROI];
int index = 0;
int seq[] = SEQ;

int takedata = 0;  // takedata has value 0 or 1 depending on whether data is being recorded
char key = '0';   // initialize command key
int timeMs;    // variable for recording time in microseconds	
int inittime;    // initial time when data collection begins
int counter = 0;    // Counts the number of images taken
FrameInfo timing;
IplImage *cvDisplay[NUM_ROI];

// allocate resources
void initialization(void) {
	// following lines are for displaying images only!  See OpenCV doc for more info.
	// they can be left out, if speed is important.
	//IplImage *cvDisplay[NUM_ROI];

#if DISPLAY_TRACKING
	cvDisplay[0] = cvCreateImageHeader(cvSize(ROI_BOX_W0, ROI_BOX_H0), 
		BITS_PER_PIXEL, NUM_CHANNELS);
	cvNamedWindow(DISPLAY0, CV_WINDOW_AUTOSIZE);

    cvDisplay[1] = cvCreateImageHeader(cvSize(ROI_BOX_W1, ROI_BOX_H1), 
		BITS_PER_PIXEL, NUM_CHANNELS);
	cvNamedWindow(DISPLAY1, CV_WINDOW_AUTOSIZE);

	cvDisplay[2] = cvCreateImageHeader(cvSize(ROI_BOX_W2, ROI_BOX_H2), 
		BITS_PER_PIXEL, NUM_CHANNELS);
	cvNamedWindow(DISPLAY2, CV_WINDOW_AUTOSIZE);
#endif
	
	
	// initialize the tracking window (i.e. blob and ROI positions)
	memset(&cur[0], 0, sizeof(TrackingWindow));
	set_initial_positions(&cur[0]);

	memset(&cur[1], 0, sizeof(TrackingWindow));
	set_initial_positions2(&cur[1]);

	memset(&cur[2], 0, sizeof(TrackingWindow));
	set_initial_positions3(&cur[2]);

	// initialize the camera
	rc = init_cam(&fg, MEMSIZE(cur[0].roi_w, cur[0].roi_h), NUM_BUFFERS, CAMLINK);
	if(rc != FG_OK) {
		printf("init: %s\n", Fg_getLastErrorDescription(fg));
		Fg_FreeGrabber(fg);
		//return rc;
	}
	// start acquiring images (this function also writes any buffered ROIs to the camera)
	rc = acquire_imgs(fg, (int *) &seq, SEQ_LEN);
	if(rc != FG_OK) {
		printf("init: %s\n", Fg_getLastErrorDescription(fg));
		Fg_FreeGrabber(fg);
		//return rc;
	}

	// initialize parameters
	//img_nr = 1;
	int initnum;

	QueryPerformanceFrequency(&timing.freq);
}

// de-allocate memory
void memclear(void) {
	// free camera resources
	rc = deinit_cam(fg);
	if(rc != FG_OK) {
		printf("deinit: %s\n", Fg_getLastErrorDescription(fg));
		//return rc;
	}
}
// get the images and process them
void takePicture(double *coords)
{
	int i;
	static int img_nr = 1;

	// start a timer
	QueryPerformanceCounter(&timing.grab_start);
	// get number of last image acquired
	img_nr = Fg_getLastPicNumberBlocking(fg, 1, PORT_A, TIMEOUT);
	// stop timer
	QueryPerformanceCounter(&timing.grab_stop);

	// record image number
	coords[12] = img_nr;
	// record image number modulo 3
	coords[13] = img_nr%3;
	// record time it took to acquire last image
	coords[14] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;

	QueryPerformanceCounter(&timing.grab_start);
	// camera has taken picture of the real ball
	if (img_nr%3 == 1) {
		cur[0].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
		img_nr = Fg_getLastPicNumberBlocking(fg, img_nr+1, PORT_A, TIMEOUT);
		cur[1].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
		img_nr = Fg_getLastPicNumberBlocking(fg, img_nr+1, PORT_A, TIMEOUT);
		cur[2].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
	}
	// camera has taken picture of the reflected ball
	else if (img_nr%3 == 2) {
		cur[1].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
		cur[0].img = (unsigned char *) Fg_getImagePtr(fg, img_nr-1, PORT_A);
		img_nr = Fg_getLastPicNumberBlocking(fg, img_nr+1, PORT_A, TIMEOUT);
		cur[2].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
	}
	// camera has taken picture of the bar
	else {
		cur[2].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);
		cur[1].img = (unsigned char *) Fg_getImagePtr(fg, img_nr-1, PORT_A);
		cur[0].img = (unsigned char *) Fg_getImagePtr(fg, img_nr-2, PORT_A);
	}
	QueryPerformanceCounter(&timing.grab_stop);
	// record time to get images
	coords[15] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;

	QueryPerformanceCounter(&timing.grab_start);
	for (index=0;index<3;index++) {
		// process image
		threshold(&cur[index], THRESHOLD);
		erode(&cur[index]);
		// calculate centroid
		centroid(&cur[index]);
		// Transform coordinates from camera frame to realworld frame
		if (index == 1) {
			trans_coords2(&cur[index]);
		}
		else {
			trans_coords(&cur[index]);
		}

		// create timestamp
		timeMs = img_nr;
		Fg_getParameter(fg, FG_TIMESTAMP, 
				&timeMs, PORT_A);
		//printf("\n%d\n", time);
		
		// updata position
		position(&cur[index]);

		// at this point position(...) has updated the ROI, but it only stores
		// the updated values internal to the code.  The next step is to flushq
		// the ROI to the camera (see position(...) documentation).

		// write ROI position to camera to be updated on frame "img_nr"
		write_roi(fg, cur[index].roi, img_nr + 6, !DO_INIT);

		// show image on screen
		if (DISPLAY_TRACKING) {
			display_tracking(&cur[index], cvDisplay[index]);
		}

		// record data for reflected ball image
		if (index%3 == 1) {
			coords[5] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
			coords[3] =	(double) cur[1].xc;
			coords[4] =	(double) cur[1].yc;
			//printf("%f,%f,%f \n",coords[3],coords[4],coords[5]);
			coords[10] = img_nr;
		}
		// record data for bar image
		else if (index%3 == 2) {
			coords[8] =	(double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
			coords[6] =	(double) cur[2].xc;
			coords[7] =	(double) cur[2].yc;
			//printf("%f,%f,%f \n",coords[6],coords[7],coords[8]);
			coords[11] = img_nr;
		}
		// record data for real ball image
		else {
			coords[2] =	(double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
			coords[0] =	(double) cur[0].xc;
			coords[1] =	(double) cur[0].yc;
			//printf("%f,%f \n",cur[0].xc,cur[0].yc);
			coords[9] = img_nr;
		}
	}
	QueryPerformanceCounter(&timing.grab_stop);
	// record time to process images
	coords[16] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;

	// old method of executing this code, wherein each time the MEX-file is accessed,
	// first one picture is taken and processed, then the next, and then the next.  That 
	// method could be sped up with the technique that is employed now.  I left the code
	// in comment below just in case it is ever needed again.
	/*
	for (i=0;i<3;i++) {
		QueryPerformanceCounter(&timing.grab_start);
		img_nr = Fg_getLastPicNumberBlocking(fg, img_nr, PORT_A, TIMEOUT);
		QueryPerformanceCounter(&timing.grab_stop);

		// Obtain index for ROI based on image number
		if (img_nr%3 == 1) {
			index = 0;
		}
		else if (img_nr%3 == 2) {
			index = 1;
		}
		else {
			index = 2;
		}
		
		cur[index].img = (unsigned char *) Fg_getImagePtr(fg, img_nr, PORT_A);

		// make sure that camera returned a valid image
		if (cur[index].img == NULL) {
			// typically this state only occurs if an invalid ROI has been programmed
			// into the camera (e.g. roi_w == 4).
			printf("img is null: %d\n", img_nr);
			//system("PAUSE");
			//break;
		}
		// process image
		threshold(&cur[index], THRESHOLD);
		erode(&cur[index]);
		// calculate centroid
		centroid(&cur[index]);
		// Transform coordinates from camera frame to realworld frame
		if (index == 1) {
			trans_coords2(&cur[index]);
		}
		else {
			trans_coords(&cur[index]);
		}

		// create timestamp
		timeMs = img_nr;
		Fg_getParameter(fg, FG_TIMESTAMP, 
				&timeMs, PORT_A);
		//printf("\n%d\n", time);
		
		// updata position
		position(&cur[index]);

		// at this point position(...) has updated the ROI, but it only stores
		// the updated values internal to the code.  The next step is to flushq
		// the ROI to the camera (see position(...) documentation).

		// write ROI position to camera to be updated on frame "img_nr"
		write_roi(fg, cur[index].roi, img_nr + 6, !DO_INIT);

		// show image on screen
		if (DISPLAY_TRACKING) {
			display_tracking(&cur[index], cvDisplay[index]);
		}

		// increment to the next desired frame.  This has to be at least
		// +2, because the camera's ROI will not be active until the second
		// frame (see Silicon Software FastConfig doc)

		//img_nr += NEXT_IMAGE;

		//QueryPerformanceCounter(&timing.grab_stop);

		if (img_nr%3 == 2) {
			coords[5] = (double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
			coords[3] =	(double) cur[1].xc;
			coords[4] =	(double) cur[1].yc;
			//printf("%f,%f,%f \n",coords[3],coords[4],coords[5]);
			coords[10] = img_nr;
		}
		else if (img_nr%3 == 0) {
			coords[8] =	(double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
			coords[6] =	(double) cur[2].xc;
			coords[7] =	(double) cur[2].yc;
			//printf("%f,%f,%f \n",coords[6],coords[7],coords[8]);
			coords[11] = img_nr;
		}
		else {
			coords[2] =	(double) (timing.grab_stop.QuadPart - timing.grab_start.QuadPart)/timing.freq.QuadPart;
			coords[0] =	(double) cur[0].xc;
			coords[1] =	(double) cur[0].yc;
			//printf("%f,%f \n",cur[0].xc,cur[0].yc);
			coords[9] = img_nr;
		}
		img_nr += NEXT_IMAGE;
	}
	*/
}

// MEX function
void mexFunction( int nlhs, mxArray *plhs[],
                  int nrhs, const mxArray *prhs[])
{
    int select;						/* input scalar */
    double *outMatrix;              /* output matrix */
    
    /* get the value of the selector  */
    select = mxGetScalar(prhs[0]);

    /* create the output matrix */
    plhs[0] = mxCreateDoubleMatrix(1,17,mxREAL);

    /* get a pointer to the real data in the output matrix */
    outMatrix = mxGetPr(plhs[0]);

	// choose which function to execute based on input from MATLAB
	if (select == 0) {
		initialization();
	}
	else if (select == 1) {
		takePicture(outMatrix);
	}
	else {
		memclear();
	}
}