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Auto Cropping- Based on Labeling the Connected Components using MATLAB

Auto Cropping Based on labeling the connected components is related to digital image processing. So, In this article, we will discuss the Auto Cropping-Based on labeling the connected components. Before that look at the basic terms which are required in this topic.

Auto Cropping

In terms of MATLAB, the auto-crop node is fix the position of inputs so that the content of the image is either focused at the center of the image without being resized. For auto-cropping, the image in MATLAB uses the below function.



imcrop()

Syntax for Labeling 

L = bwlabel(BW)      % return the label matrix that contains labels 
                                         for the 8-connected object found.
                 
L = bwlabel(BW, con)     % return the label matrix where specify 
                                             the con connectivity.



[L,n] = bwlabel(__)          %label function also return number of object
                                            found in BW.

Suppose in an image all pixels are connected components that show similar intensity values.

Example 1:




% MATLAB code for the binary image
% using 4-connected components
% Labeling -Code
clc;
clear all;
close all;
warning off;
a= [1 1 1 0 0 0 0 0
    1 1 1 0 1 1 0 0
    1 1 1 0 1 1 0 0
    1 1 1 0 0 0 1 0
    1 1 1 0 0 0 1 0
    1 1 1 0 0 0 1 0
    1 1 1 0 0 1 1 0
    1 1 1 0 0 0 0 0];  
     
% binary image.
[x,y]= bwlabel(a,8); 
 % two input parameters one
 % is binary image and another is set value.

Output:

 

Example 2:




%  Auto crop image via built-in function imcrop()
% Read the image
im = imread('GeeksforGeeks.png'); 
 
 % show the image in figure
imshow(im);  
pause(1)
 
% crop the image via crop function
imcrop = imcrop(im,[20 30 40 80]);   
imshow(imcrop);

imread() is used to reads the image from the file specified filename. Without the crop, the image shows the using imshow() function.

Output:

 

Now you can see the Auto crop image using the crop function with different intensity values.

 

If we changed the intensity value of the crop function then you will get a different figure as output.

imcrop = imcrop(im,[1090 200 3000 400]); 

 


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