A16 - Image Color Segmentation

September 2, 2008

Suppose I have a reference image Mpatch and an image I want to segment M, they have NCC (normalized chromaticidty coordinates) components rpatch, gpatch and bpatch, and r, g, and b

Code for non-parametric image segmentation by color:


delta_pix = 0.01;
val=[];

num_=[];

num=[];

counter=1;

for i=0:delta_pix:1;

[x,y]=find((rpatch>=i) & (rpatch<(i+delta_pix)));

val(counter)=i;

num_(counter)=length(x);

counter=counter+1;

end

num = num_./((size(rpatch,1))*size(rpatch,2));

plot(val, num_);

B = zeros(size(M,1),size(M,2),3);
delta_pix = 0.01;

val=[];

num_=[];

num=[];

counter=1;

for i=0:delta_pix:1;

[x,y]=find((gpatch>=i) & (gpatch<(i+delta_pix)));

val(counter)=i;

num_(counter)=length(x);

counter=counter+1;

end

num = num_./((size(gpatch,1))*size(gpatch,2));

plot(val, num_);

for i = 0:delta_pix:1

[x,y] = find((g>=i) & (g<(i+delta_pix)));

for k=1:length(x) for l=1:length(y)

B(x(k),y(l),2) = num_((i+delta_pix)/delta_pix);

end

end

i

end
B(:,:,3) = 1-B(:,:,1)-B(:,:,2);

Code for parametric segmentation:

delta_pix = 0.01;
val=[];

num_=[];

PDF = [];

counter=1;

for i=0:delta_pix:1;

[x,y]=find((rpatch>=i) & (rpatch<(i+delta_pix)));

val(counter)=i;

num_(counter)=length(x);

counter=counter+1;

end

PDF = num_./((size(rpatch,1))*size(rpatch,2));

plot(val, PDF);

mn = find(PDF==max(PDF));

mu_red = val(mn);

sigma_red = stdev(PDF);
val=[];

num_=[];

PDF = [];

counter=1;

for i=0:delta_pix:1;

[x,y]=find((gpatch>=i) & (gpatch<(i+delta_pix)));

val(counter)=i;

num_(counter)=length(x);

counter=counter+1;

end

PDF = num_./((size(gpatch,1))*size(gpatch,2));

plot(val,PDF);

mn = find(PDF==max(PDF));

mu_green = val(mn);

sigma_green = stdev(PDF);
x = [0:delta_pix:1];

pr = (exp(-((x-mu_red)^2)/(2*sigma_red)))/(sigma_red*sqrt(2*%pi));

pg = (exp(-((x-mu_green)^2)/(2*sigma_green)))/(sigma_green*sqrt(2*%pi));

K = zeros(size(M,1),size(M,2));

for i = 0:delta_pix:1

[x,y] = find((r>=i) & (r<(i+delta_pix)));

for k=1:length(x)

for l=1:length(y)

green = round(g(x(k),y(k)));

probability = pr((i+delta_pix)/delta_pix)*pg((green+delta_pix)/delta_pix);

K(x(k),y(l)) = probability;

end

end

i

end

Display

G = im2gray(B);

L = im2gray(M);

subplot(311)

imshow(L,[]);

subplot(312)

imshow(G,[]);

Figure 1. The raw image.

Figure 2. The reference patch which belongs to the hand.

Figure 3. The raw image (top) and the maps showing the probability that a pixel belongs to the region of interest which in this case is the skin. The center image is the result of non-parametric image segmentation while the bottom image is the result of parametric image-segmentation.

Self-grade: 10/10 because I was able to finish the activity on time and my parametric and non-parametric image segmentations result looks reasonable

Thank you, Lei for helping me with histogramming.