Applying Blob Detection Technique to the Original Image 2

clc;
clear all;
originalImage = imread('coins.png');
subplot(3, 3, 1);
imshow(originalImage);
% Maximize the figure window.
set(gcf, 'Position', get(0, 'ScreenSize'));
[pixelCount grayLevels] = imhist(originalImage);
subplot(3, 3, 2);
bar(pixelCount); title('Histogram of original image');
xlim([0 grayLevels(end)]); % Scale x axis manually.
  thresholdValue = 100;
  binaryImage = originalImage > thresholdValue;



binaryImage = imfill(binaryImage, 'holes');
% Display the binary image.
subplot(3, 3, 3); imagesc(binaryImage); colormap(gray(256)); title('Binary Image, obtained by thresholding'); axis square;
labeledImage = bwlabel(binaryImage, 8);    
% Label each blob so we can make measurements of it
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle');
% pseudo random color labels
subplot(3, 3, 4); imshow(labeledImage, []);
title('Labeled Image, from bwlabel()');
axis square; subplot(3, 3, 5); imagesc(coloredLabels);
axis square;
caption = sprintf('Pseudo colored labels, from label2rgb().\nBlobs are numbered from top to bottom, then from left to right.');
title(caption);
blobMeasurements = regionprops(labeledImage, originalImage, 'all');  
numberOfBlobs = size(blobMeasurements, 1);
subplot(3, 3, 6); imagesc(originalImage);
title('Outlines, from bwboundaries()'); axis square; hold on;
boundaries = bwboundaries(binaryImage);
numberOfBoundaries = size(boundaries);

for k = 1 : numberOfBoundaries
thisBoundary = boundaries{k};
plot(thisBoundary(:,2), thisBoundary(:,1), 'g', 'LineWidth', 2);
end
hold off;

Applying Blob Detection Technique to the Original Image

clc;

clear all;

originalImage = imread('coins.png');

subplot(3, 3, 1);

imshow(originalImage);

% Maximize the figure window.

set(gcf, 'Position', get(0, 'ScreenSize'));

[pixelCount grayLevels] = imhist(originalImage);

subplot(3, 3, 2);

bar(pixelCount); title('Histogram of original image');

xlim([0 grayLevels(end)]); % Scale x axis manually.

thresholdValue = 100;

binaryImage = originalImage > thresholdValue;

binaryImage = imfill(binaryImage, 'holes');

% Display the binary image.

subplot(3, 3, 3); imagesc(binaryImage); colormap(gray(256)); title('Binary Image, obtained by thresholding'); axis square;

labeledImage = bwlabel(binaryImage, 8); 

coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle');

subplot(3, 3, 4);              imshow(labeledImage, []);          

title('Labeled Image, from bwlabel()');

axis square;      subplot(3, 3, 5);                                

imagesc(coloredLabels);

axis square;

caption = sprintf('Pseudo colored labels, from label2rgb().\nBlobs are numbered from top to bottom, then from left to right.');

title(caption);

blobMeasurements = regionprops(labeledImage, originalImage, 'all');  

numberOfBlobs = size(blobMeasurements, 1);

subplot(3, 3, 6); imagesc(originalImage);

title('Outlines, from bwboundaries()'); axis square;       hold on;

boundaries = bwboundaries(binaryImage);      

numberOfBoundaries = size(boundaries);

for k = 1 : numberOfBoundaries

              thisBoundary = boundaries{k};

              plot(thisBoundary(:,2), thisBoundary(:,1), 'g', 'LineWidth', 2);

end

hold off;

Applying Corner Detection Technique to the Original Image

I = checkerboard(50,2,2);

C = corner(I);

imshow(I);

hold on

plot(C(:,1), C(:,2), 'r*');

Applying Watershed Segmentation to the Original Image

I = imread('image.jpg');

subplot(1,2,1); imshow(I); title('Original Image');

se = strel('diamond',7);

Itop = imtophat(I,se);

Ibot = imbothat(I,se);

Ienhance = imsubtract(imadd(Itop,30), Ibot);

Iec = imcomplement(Ienhance);

Iemin = imextendedmin(Iec,22);

Iimpose = imimposemin(Iec,Iemin);

Iwat = watershed(Iimpose);

Iseg = label2rgb(Iwat);

subplot(1,2,2); imshow(Iseg); title('Watershed Segmented Image');

Applying Dilation and Erosion to the Original Image

Lenna = imread('lenna2.jpg');

SE3 = strel('square',3);

SE5 = strel('square',5);                                   

SE7 = strel('square',7);

ErodeLenna = imerode(Lenna,SE3);

subplot(2,3,1); imshow(ErodeLenna);  ylabel('Eroded Image'); title('5x5');

ErodeLenna = imerode(Lenna,SE5);

subplot(2,3,2); imshow(ErodeLenna); title('5x5');

ErodeLenna = imerode(Lenna,SE7);

subplot(2,3,3); imshow(ErodeLenna); title('7x7');

Converting Grayscale Image into Binary Image (Black-White)

Lenna = imread('lenna.png');

GrayLenna = rgb2gray(Lenna);

bwLenna = im2bw(GrayLenna);

subplot(1,2,1); imshow(bwLenna);                          

subplot(1,2,2); imhist(bwLenna)

Creating a Histogram of an Original Image

Lenna = imread('lenna.png');                                                     

GrayLenna = rgb2gray(Lenna);

imhist(GrayLenna)