Region-Based Segmentation with examples in DIP and its implementation in MATLAB|Growing|Split|Merge

Video lecture series on Digital Image Processing, Lecture: 52, Region-Based Segmentation with examples in DIP and its implementation in MATLAB|Growing|Split|Merge What is Region based segmentation? Why do we use Region based segmentation? What is Region Growing? What is Region Splitting? What is Region Merging? What is Region Splitting and Merging? Link to download ppts/lecture notes: drive.google.com/drive/folders/1AtR1eq6ZvQf-5vjXEM… #DIP #DIPwithMATLAB #DigitalImageProcessingUsingMATLAB #DigitalImageProcessing #StudywithDrDafda MATLAB code used in the video is given below: % MATLAB code for Region Growing and Region based Segmentation % By comparing every unallocated neighbouring pixels to the region, % the region is iteratively grown. As a measure of similarity, % the difference between a pixel's intensity value and the region's mean % is employed. pixel with the most minimal difference is allocated to % the appropriate location when measured in this way. When the intensity % difference between the region mean and the new pixel reaches a specified % threshold (reg_max), this procedure comes to an end. close all; clear all; clc; I = im2double(imread('coins.png')); subplot(1,3,1);imshow(I);title('Original Image'); x=125; y=125; % the position of the seedpoint reg_max = 0.2; % region maximum intensity (defaults to 0.2) J = zeros(size(I)); % Output (Region Grown Image) Isizes = size(I); % Dimensions of input image reg_mean = I(x,y); % The mean of the segmented region reg_size = 1; % Number of pixels in region % Free memory to store neighbours of the (segmented) region neg_free = 10000; neg_pos=0; neg_list = zeros(neg_free,3); pixdist=0; % Distance of the region newest pixel to the regio mean % Neighbor locations (footprint) neigb=[-1 0; 1 0; 0 -1;0 1]; % Start region growing until distance between region and posible new pixels % become higher than a certain treshold while(pixdist{less than}reg_max && reg_size{less than}numel(I)) % Add new neighbors pixels for j=1:4 % Calculate the neighbour coordinate xn = x +neigb(j,1); yn = y +neigb(j,2); % Check if neighbour is inside or outside the image ins=(xn{greater than and equal to}1)&&(yn{greater than and equal to}1)&&(xn{less than and equal to}Isizes(1))&&(yn{less than and equal to}Isizes(2)); % Add neighbor if inside and not already part of the segmented area if(ins&&(J(xn,yn)==0)) neg_pos = neg_pos+1; neg_list(neg_pos,:) = [xn yn I(xn,yn)]; J(xn,yn)=1; end end % Add a new block of free memory if(neg_pos+10{greater than}neg_free), neg_free=neg_free+10000; neg_list((neg_pos+1):neg_free,:)=0; end % Add pixel with intensity nearest to the mean of the region, to the region dist = abs(neg_list(1:neg_pos,3)-reg_mean); [pixdist, index] = min(dist); J(x,y)=2; reg_size=reg_size+1; % Calculate the new mean of the region reg_mean= (reg_mean*reg_size + neg_list(index,3))/(reg_size+1); % Save the x and y coordinates of the pixel (for the neighbour add proccess) x = neg_list(index,1); y = neg_list(index,2); % Remove the pixel from the neighbour (check) list neg_list(index,:)=neg_list(neg_pos,:); neg_pos=neg_pos-1; end subplot(1,3,2);imshow(J);title('Region Grown Image') % Make the segmented area as logical matrix J=J{greater than}1; subplot(1,3,3);imshow(I+J);title('Segmented Image') impixelinfo;

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