Time Delay Measurement in MATLAB

Hello All,
I am trying to measure fluid velocity in an AVI file, and am doing this by converting each frame to an image and measuring the mean intensity of the pixels in two different windows spaced out. Now that I have two different signals that should be theoretically time delayed, I need to cross correlate them to see the time delay, but I am having trouble with xcorr. I seem to obtain the signals alright, but the xcorr always says that the delay is the number of frames I test (when t=1:30, the delay is 30, when t=1:400, the delay is 400). My code is posted below:

%Splits frames of AVI into grayscale images. Then it takes pixel intensity
%averages of the windows and inputs into two arrays AllIntensity1 and
%AllIntensity2. Then it cross correlates the signals.

A=mmreader('new.avi') %Reads Avi movie, places into A.mov for Matlab's
%viewing pleasure.

for t=1:30
im = read( A, t);%reads sequential frames
imgray=rgb2gray(im);%converts read images into grayscale

%Chooses windows in first iteration only
if (t==1)
BW1=roipoly(imgray);
BW2=roipoly(imgray);
end
%computes mean intensity for each window separately, placing in two
%arrays
Stats=regionprops(BW1,imgray,'MeanIntensity');
AllIntensity1(t)=Stats.MeanIntensity;
Stats=regionprops(BW2,imgray,'MeanIntensity');
AllIntensity2(t)=Stats.MeanIntensity;

end
AllIntensity2=[100 100 103 105 103 100 AllIntensity1(1:24)];

%%%%%%%%%%%%%%%%%%%%%%%%%%%Cross Correlation Begins%%%%%%%%%%%%%%%%%%%%%%%%
xc=xcorr(AllIntensity1,AllIntensity2,'coeff');
[a,delay]=max(xc);
a
delay
subplot(311),plot(AllIntensity1)
subplot(312),plot(AllIntensity2)
subplot(313),plot(xc(1:59))

Any Ideas?? Thanks!
Steve Start a New Thread

Steve-

Are you cross correlating the entire image, or only the extracted particle (or other marker) from the fluid flow? If
the entire image, then are there multiple particles? If so should they all be moving at the same speed?

One way to test your code would be to create simulated images; for example, place a pattern (circle, etc) in the
center of image 1, then move it slightly over and down in image 2, then run xcorr(). You should get an x-y offset in
pixels.

-Jeff

> I am trying to measure fluid velocity in an AVI file, and am doing
> this by converting each frame to an image and measuring the mean
> intensity of the pixels in two different windows spaced out. Now
> that I have two different signals
> that should be theoretically time delayed, I need to cross
> correlate them to see the time delay, but I am having trouble with
> xcorr. I seem to obtain the signals alright, but the xcorr always
> says that the delay is the number of frames I test (when t=1:30,
> the delay is 30, when t=1:400, the delay is 400). My code is posted below:
>
> %Splits frames of AVI into grayscale images. Then it takes pixel intensity
> %averages of the windows and inputs into two arrays AllIntensity1 and
> %AllIntensity2. Then it cross correlates the signals.
>
> A=mmreader('new.avi') %Reads Avi movie, places into A.mov for Matlab's %viewing pleasure.
>
> for t=1:30
> im = read( A, t);%reads sequential frames
> imgray=rgb2gray(im);%converts read images into grayscale
>
> %Chooses windows in first iteration only
> if (t==1)
> BW1=roipoly(imgray);
> BW2=roipoly(imgray);
> end
> %computes mean intensity for each window separately, placing in two %arrays
> Stats=regionprops(BW1,imgray,'MeanIntensity');
> AllIntensity1(t)=Stats.MeanIntensity;
> Stats=regionprops(BW2,imgray,'MeanIntensity');
> AllIntensity2(t)=Stats.MeanIntensity;
>
> end
> AllIntensity2=[100 100 103 105 103 100 AllIntensity1(1:24)];
>
> %%%%%%%%%%%%%%%%%%%%%%%%%%%Cross Correlation Begins%%%%%%%%%%%%%%%%%%%%%%%%
xc=xcorr(AllIntensity1,AllIntensity2,'coeff');
> [a,delay]=max(xc);
> a
> delay
> subplot(311),plot(AllIntensity1)
> subplot(312),plot(AllIntensity2)
> subplot(313),plot(xc(1:59))
>
> Any Ideas?? Thanks!
> Steve
> Start a New Thread

Steve-

> I am only cross correlating two windows of the images, mainly the edges. The
> windows sense the pixel changes so it can track lighter particles (due to
> gaps between red blood cells) moving through both windows, and the cross
> correlation should measure the time it takes to go from one window to the
> next.

"...the cross correlation should measure the time it takes to go from one
window to the next."

At first glance, this sounds like it explains why you always get the number of frames as a delay value. You're not
actually measuring the movement of a particle within one image.

-Jeff

> On Mon, Aug 17, 2009 at 8:39 AM, Jeff Brower wrote:
>
>> Steve-
>>
>> Are you cross correlating the entire image, or only the extracted particle
>> (or other marker) from the fluid flow? If
>> the entire image, then are there multiple particles? If so should they all
>> be moving at the same speed?
>>
>> One way to test your code would be to create simulated images; for example,
>> place a pattern (circle, etc) in the
>> center of image 1, then move it slightly over and down in image 2, then run
>> xcorr(). You should get an x-y offset in
>> pixels.
>>
>> -Jeff
>>
>> > I am trying to measure fluid velocity in an AVI file, and am doing
>> > this by converting each frame to an image and measuring the mean
>> > intensity of the pixels in two different windows spaced out. Now
>> > that I have two different signals
>> > that should be theoretically time delayed, I need to cross
>> > correlate them to see the time delay, but I am having trouble with
>> > xcorr. I seem to obtain the signals alright, but the xcorr always
>> > says that the delay is the number of frames I test (when t=1:30,
>> > the delay is 30, when t=1:400, the delay is 400). My code is posted
>> below:
>> >
>> > %Splits frames of AVI into grayscale images. Then it takes pixel
>> intensity
>> > %averages of the windows and inputs into two arrays AllIntensity1 and
>> > %AllIntensity2. Then it cross correlates the signals.
>> >
>> > A=mmreader('new.avi') %Reads Avi movie, places into A.mov for Matlab's
>> %viewing pleasure.
>> >
>> > for t=1:30
>> > im = read( A, t);%reads sequential frames
>> > imgray=rgb2gray(im);%converts read images into grayscale
>> >
>> > %Chooses windows in first iteration only
>> > if (t==1)
>> > BW1=roipoly(imgray);
>> > BW2=roipoly(imgray);
>> > end
>> > %computes mean intensity for each window separately, placing in two
>> %arrays
>> > Stats=regionprops(BW1,imgray,'MeanIntensity');
>> > AllIntensity1(t)=Stats.MeanIntensity;
>> > Stats=regionprops(BW2,imgray,'MeanIntensity');
>> > AllIntensity2(t)=Stats.MeanIntensity;
>> >
>> > end
>> > AllIntensity2=[100 100 103 105 103 100 AllIntensity1(1:24)];
>> >
>> > %%%%%%%%%%%%%%%%%%%%%%%%%%%Cross Correlation
>> Begins%%%%%%%%%%%%%%%%%%%%%%%%
>> xc=xcorr(AllIntensity1,AllIntensity2,'coeff');
>> > [a,delay]=max(xc);
>> > a
>> > delay
>> > subplot(311),plot(AllIntensity1)
>> > subplot(312),plot(AllIntensity2)
>> > subplot(313),plot(xc(1:59))
>> >
>> > Any Ideas?? Thanks!
>> > Steve Start a New Thread