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来自「hopfield neural network for binary image」· HTML 代码 · 共 69 行
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<html><head><title>Example of edge detection, edge linking, and line segment fitting</title></head><body bgcolor="#ffffff" vlink="#ff0000"><h2>Example of edge detection, edge linking, and line segment fitting</h2><hr><center><img src=shapessm.jpg></center><pre> % Read the sample image in im = imread('shapessm.jpg'); % Find edges using the Canny operator with hysteresis thresholds of 0.1 % and 0.2 with smoothing parameter sigma set to 1. edgeim = edge(im,'canny', [0.1 0.2], 1); figure(1), imshow(edgeim);</pre><p><center><img src=edgeim.jpg></center><pre> % Link edge pixels together into lists of sequential edge points, one % list for each edge contour. A contour/edgelist starts/stops at an % ending or a junction with another contour/edgelist. % Here we discard contours less than 10 pixels long. [edgelist, labelededgeim] = edgelink(edgeim, 10); % Display the edgelists with random colours for each distinct edge % in figure 2 drawedgelist(edgelist, size(im), 1, 'rand', 2); axis off </pre><center><img src=edgelistim.jpg></center><pre> % Fit line segments to the edgelists tol = 2; % Line segments are fitted with maximum deviation from % original edge of 2 pixels. seglist = lineseg(edgelist, tol); % Draw the fitted line segments stored in seglist in figure window 3 with % a linewidth of 2 and random colours drawedgelist(seglist, size(im), 2, 'rand', 3); axis off</pre><center><img src=segmentim.jpg></center><hr></body></html>⌨️ 快捷键说明
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