Histogram Processing in MATLAB

     Read and Plot the histogram of dark, bright, Low contrast and High contrast image without using built-in function. Verify with the built-in function imhist.

       CODE :

clc; clear all;
img1=imread('hist1.jpg');
img2=imread('hist2.jpg');
img3=imread('hist3.jpg');
img4=imread('hist4.jpg');
subplot(431), imshow(img1), title('Dark image')
subplot(434), imshow(img2), title('Bright image')
subplot(437), imshow(img3), title('Low contrast image')
subplot(4,3,10), imshow(img4), title('High contrast image')

for a=2:3:11
    if(a==2)
        img=img1;
    elseif(a==5)
        img=img2;
    elseif(a==8)
        img=img3;
    else
        img=img4;
    end

[M, N]=size(img);
histbar=zeros(1,256);
for i=1:M
    for j=1:N
            v=img(i,j);
            histbar(v+1)=histbar(v+1)+1;
    end
end
subplot(4,3,a), bar(histbar);
if (a==2), title('Histogram Using code'); end
subplot(4,3,a+1), imhist(img);
if (a==2), title('Histogram using Built-in function'); end
end

OUTPUT RESULT :

Connectivity in MATLAB

Create a checker board pattern and count the number of objects using 4 and 8 connectivity.

MATLAB CODE:

I=checkerboard(20);

figure,imshow(I);

[l,num]=bwlabel(I);                       % check the number of objects using 4 and 8 connectivity

RGB=label2rgb(bwlabel(I));   % Display the objects using conversion label2rgb

figure,imshow(RGB)

Checkerboard Pattern

Connected Components

CONCLUSION:

A checkerboard pattern was created and the connected objects were found using 8 - connectivity. All the connected objects were displayed using an RGB representation as shown in Fig. 1