How to count white pixels in Watershed segmented image?

I am using watershed method to this image:

And got the output:

Now I want to convert the segmented part within the yellow boundary to black and white, and calculate its white and black pixels within the boundary. How can I do it?

The part of the code is as follows:

[B,L]=bwboundaries(tumor,'noholes'); %draw boundaries around the tumor

imshow(image);
hold on
for i=1:length(B)
 plot(B{i}(:,2),B{i}(:,1), 'y' ,'linewidth',1.45);
 end
title('Segmented Tumor');
hold off;

Answer 1

[Image Analyst]

What is the intensity that distinguishes between your "black" and "white"? 128? Don't use image as the name of your variable -- it's already the name of a built-in function.

Anyway to get the pixel values for blob in L:

pixelValues = grayScaleImage(L == 1); % A 1-D vector of all the pixel values in the region.
% Then sum up black and white
threshold = 128; % Whatever you want.
numBlackPixels = sum(pixelValues < threshold)
numWhitePixels = sum(pixelValues >= threshold)

[Tawsif Mostafiz]

@Image Analyst I have changed the code a little bit for better understanding. I have converted it to black and white using following:

bw=im2bw(grayScaleImage,0.15); %0.15 is the threshold value
[B,L]=bwboundaries(tumor,'noholes'); %draw boundaries around the tumor
imshow(bw);
hold on
for i=1:length(B)
 plot(B{i}(:,2),B{i}(:,1), 'r' ,'linewidth',1.45);
 end
title('Segmented Tumor');
hold off;

Now, the output is following:

Now, I want to count the white pixels and black pixels within the red border. Extremely sorry for being vague previously. How do I do that?

[Image Analyst]

Try this:

thisBoundary = B{1}; % Whatever boundary you want.
x = thisBoundary(:, 2);
y = thisBoundary(:, 1);
redMask = poly2mask(x, y, rows, columns);
pixelsInRedMask = binaryImage(redMask);
numBlack = sum(pixelsInRedMask == 0);
numWhite = sum(pixelsInRedMask == 1);

Answer 2

[darova]

Here is an example with using bwlabel

A = zeros(100);
t = linspace(0,2*pi,1000);      % a lot of points
[x,y] = pol2cart(t,1);          % circle coordinates
ind = sub2ind(size(A),round(y*15)+30,round(x*25)+50);       % convert coordinates into [rows,cols]
A(ind) = 1;                     % fill [rows,cols] with ones
A1 = imdilate(A,ones(2));       % make line thicker (bwlabel doesn't work for thin lines)
[B,n] = bwlabel(~A1);           % separate each region
imshow(B,hot(2))                % show separated region
line(x*25+50,y*15+30)           % show original curve