How to compare two images from each other: Round 2

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Hello again!
Slightly stuck on this issue. I need help on finding a way for MatLab to follow an object from one picture to the next, automatically. I've written a small script from help online that allows me to select the object and determine its coordinates, but is there a way that MatLab can see the object without me manually tracing it?
I = imread('rice.png');
background = imopen(I,strel('disk',15));
figure, surf(double(background(1:8:end,1:8:end))),zlim([0 255]);
%%Darkens image
I2 = I - background;
%figure, imshow(I2)
%%Increases contrast
I3 = imadjust(I2);
%figure, imshow(I3);
%%Turns image into binary colors (Black and White)
level = graythresh(I3);
bw = im2bw(I3,level);
bw = bwareaopen(bw, 50);
%%figure, imshow(bw)
cc = bwconncomp(bw, 4);
%%Select grain connected to background
grain = false(size(bw));
grain(cc.PixelIdxList{50}) = true;
figure, imshow(grain);
labeled = labelmatrix(cc);
whos labeled
%%Color Shift
RGB_label = label2rgb(labeled, @autumn, 'c', 'shuffle');
figure, imshow(RGB_label)
graindata = regionprops(cc, 'basic');
%%Grain area
grain_areas = [graindata.Area];
[max_area, idx] = max(grain_areas);
grain = false(size(bw));
grain(cc.PixelIdxList{idx}) = true;
figure, imshow(grain)
%%Select a portion to allocate coordinates of object
[x, y, ~, xi, yi] = roipoly(grain);
BW = roipoly(100, 200, xi, yi);
%%Displays xi, yi coordinates
figure, imshow(BW)
grain2 = imread('Rice3.gif');
[x2,y2,Bw,xi2, yi2] = roipoly(grain2);
  1 Comment
Frank on 13 May 2011
My goal for this is to track the object and calculate how much it has moved from picture to picture

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Accepted Answer

Sean de Wolski
Sean de Wolski on 13 May 2011
For this rice example, what do you know about that grain that makes it different that the rest?
  • Its size (+- a few pixels due to digitization)
  • The area of its boundingbox
  • Eccentricity
These are just three options of:
doc regionprops
that could be used.
  • Basically you would isolate the object you want in the first image.
  • Run the same binarization operation on the second image
  • do a connected components analysis in both, keeping the connected component of interest in the first one. (doc bwconncomp)
  • Get the measurements of all objects in the second image.
  • Whichever one is the most similar is your match.
Note: these are just a few of the things you could do. Looking at your above binary image, binarized, they seem feasible. If you want to compare in non-binary images then we might have to figure out something a little more complicated.
By the way, well written question - this is what allows you get a good answer

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