back_seg_code.zip_back_back images_fusion

function [obj_img] = fuzzy_segment2(image1, image2,tol,mult); rgb_img1 = imread(image1); rgb_img2 = imread(image2); gray_img = double(rgb2gray(rgb_img1)); [M,N,P] = size(rgb_img1); figure(1); %draw 2 polygons- in case of disjoint background t_inds1 = find(roipoly(rgb_img1)); t_inds2 = find(roipoly(rgb_img1)); t_inds = [t_inds1; t_inds2]; disp('performing classification...'); res_img1 = []; res_img2 = []; if (mult==0) res_img1 = classify_img(rgb_img1,t_inds,tol); res_img2 = classify_img(rgb_img2,t_inds,tol); else res_img1 = classify_img(rgb_img1,t_inds,tol); res_img2 = classify_img(rgb_img2,t_inds,tol); end disp('formatting results...'); totres = round(256*(res_img1+2*res_img2)/3); figure(2); imagesc(totres); imwrite(uint8(totres),'results/totres.png','png'); title('classification results, segment2'); colormap(gray); objimg1 = (totres == 0); %find pixels with background classification, %which are connected to first training pixel ind1n = floor(t_inds(1)/M) + 1; ind1m = mod(t_inds(1),M) + 1; objimg2 = 1 - double(bwselect([1-objimg1],ind1n,ind1m,8)); figure(3); obj_img = double(bwselect(objimg2,8)); %display segmentation mask imagesc(obj_img); colormap(gray); title('final mask, segment2');