help with bwboundaries() function ?

i use this code it run well but i cant isolate the area i selected

how i cant do that

I = imread('tamp9f.png');
Icrop = imcrop(I);

bw = im2bw(Icrop);
imshow(bw);  pause;

Ifill = imfill(bw,'holes');
imshow(Ifill);  pause;

Iarea = bwareaopen(Ifill,10000);
imshow(Iarea); pause;

boundary = bwboundaries(Iarea);
b = boundary{1};
imshow(Ifill); hold on; 
plot(b(:,2),b(:,1),'g','LineWidth',3);

you can see this http://www.mathworks.com/matlabcentral/answers/24041-cut-an-image i want to

Answer 1

[Image Analyst]

Please define "isolate".

[Isee You]

get the part of image that content the selected part of image so i can use it in my process

[Image Analyst]

Depends on what you mean by "the part of the image". If you want the bounding box, just call regionprops() and ask for the bounding box, and use imcrop() to cut it out. If you just want a list of all the pixels in the irregular-shaped blobs, then ask regionprops for PixelList, or get it from the image yourself:

thePixels = Icrop(bw);

[Isee You]

i want to get this image http://www.mediafire.com/view/?d11dd03yhx8z45w

[Image Analyst]

Okay. And......?

[Isee You]

just that.

[Image Analyst]

So do it. It looks like your code matches the code from the "Accepted" answer so it should give the image that answer gave. Does it not?

[Isee You]

i get from my code this image http://www.mediafire.com/view/?l43rwvmlk46jy8g

but i cant get this image http://www.mediafire.com/view/?d11dd03yhx8z45w "i use paint to draw it "

[Image Analyst]

Run this demo to see how to extract the largest blob:

function ExtractBiggestBlob()
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures if you have the Image Processing Toolbox.
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;

% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'coins.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage);
% Display the original gray scale image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Give a name to the title bar.
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off')

% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(grayImage);
subplot(2, 2, 2);
bar(pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.

% Threshold the image to binarize it.
binaryImage = grayImage > 100;
% Fill holes
binaryImage = imfill(binaryImage, 'holes');
% Display the image.
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize);

% Get all the blob properties.  Can only pass in originalImage in version R2008a and later.
[labeledImage, numberOfBlobs] = bwlabel(binaryImage);
blobMeasurements = regionprops(labeledImage, 'area', 'Centroid');
% Get all the areas
allAreas = [blobMeasurements.Area] % No semicolon so it will print to the command window.
menuOptions{1} = '0'; % Add option to extract no blobs.
% Display areas on image
for k = 1 : numberOfBlobs           % Loop through all blobs.
  thisCentroid = [blobMeasurements(k).Centroid(1), blobMeasurements(k).Centroid(2)];
  message = sprintf('Area = %d', allAreas(k));
  text(thisCentroid(1), thisCentroid(2), message, 'Color', 'r');
  menuOptions{k+1} = sprintf('%d', k);
end

% Ask user how many blobs to extract.
numberToExtract = menu('How many do you want to extract', menuOptions) - 1;

% Ask user if they want the smallest or largest blobs.
promptMessage = sprintf('Do you want the %d largest, or %d smallest, blobs?',...
  numberToExtract, numberToExtract);
titleBarCaption = 'Largest or Smallest?';
sizeOption = questdlg(promptMessage, titleBarCaption, 'Largest', 'Smallest', 'Cancel', 'Largest');
if strcmpi(sizeOption, 'Cancel')
  return;
elseif strcmpi(sizeOption, 'Smallest')
  % If they want the smallest, make the number negative.
  numberToExtract = -numberToExtract;
end

%---------------------------------------------------------------------------
% Extract the largest area using our custom function ExtractNLargestBlobs().
% This is the meat of the demo!
biggestBlob = ExtractNLargestBlobs(binaryImage, numberToExtract);
%---------------------------------------------------------------------------

% Display the image.
subplot(2, 2, 4);
imshow(biggestBlob, []);
% Make the number positive again.  We don't need it negative for smallest extraction anymore.
numberToExtract = abs(numberToExtract);
if numberToExtract == 1
  caption = sprintf('Extracted %s Blob', sizeOption);
elseif numberToExtract > 1
  caption = sprintf('Extracted %d %s Blobs', numberToExtract, sizeOption);
else % It's zero
  caption = sprintf('Extracted 0 Blobs.');
end
title(caption, 'FontSize', fontSize);
msgbox('Done with demo!');

% Function to return the specified number of largest or smallest blobs in a binary image.
% If numberToExtract > 0 it returns the numberToExtract largest blobs.
% If numberToExtract < 0 it returns the numberToExtract smallest blobs.
% Example: return a binary image with only the largest blob:
%   binaryImage = ExtractNLargestBlobs(binaryImage, 1)
% Example: return a binary image with the 3 smallest blobs:
%   binaryImage = ExtractNLargestBlobs(binaryImage, -3)
function binaryImage = ExtractNLargestBlobs(binaryImage, numberToExtract)
try
  % Get all the blob properties.  Can only pass in originalImage in version R2008a and later.
  [labeledImage, numberOfBlobs] = bwlabel(binaryImage);
  blobMeasurements = regionprops(labeledImage, 'area');
  % Get all the areas
  allAreas = [blobMeasurements.Area];
  if numberToExtract > 0
    % For positive numbers, sort in order of largest to smallest.
    % Sort them.
    [sortedAreas, sortIndexes] = sort(allAreas, 'descend');
  elseif numberToExtract < 0
    % For negative numbers, sort in order of smallest to largest.
    % Sort them.
    [sortedAreas, sortIndexes] = sort(allAreas, 'ascend');
    % Need to negate numberToExtract so we can use it in sortIndexes later.
    numberToExtract = -numberToExtract;
  else
    % numberToExtract = 0.  Shouldn't happen.  Return no blobs.
    binaryImage = false(size(binaryImage));
    return;
  end
  % Extract the "numberToExtract" largest blob(a)s using ismember().
  biggestBlob = ismember(labeledImage, sortIndexes(1:numberToExtract));
  % Convert from integer labeled image into binary (logical) image.
  binaryImage = biggestBlob > 0;
catch ME
  errorMessage = sprintf('Error in function ExtractNLargestBlobs().\n\nError Message:\n%s', ME.message);
  fprintf(1, '%s\n', errorMessage);
  uiwait(warndlg(errorMessage));
end

[Isee You]

thanks alot