// 6. Threshold processed = edges > 50; imshow(processed); end
// Gradient magnitude edge_magnitude = sqrt(Gx.^2 + Gy.^2); imshow(uint8(edge_magnitude)); // Prewitt prewitt_x = [-1 0 1; -1 0 1; -1 0 1]; // Laplacian (second derivative) laplacian = [0 -1 0; -1 4 -1; 0 -1 0]; edges_laplacian = imfilter(gray_img, laplacian); 7. Morphological Operations Requires binary images. digital image processing using scilab pdf
Article ID: DIP-SCILAB-01 Target Audience: Engineering students, researchers, hobbyists Software Required: Scilab 6.1+ with SIVP (Scilab Image and Video Processing) toolbox 1. Introduction Digital Image Processing (DIP) involves manipulating digital images using computer algorithms. While MATLAB is the industry standard, Scilab —a free, open-source alternative—provides powerful capabilities for DIP through its SIVP (Scilab Image and Video Processing) toolbox and core functions. // Write image to disk imwrite(img, 'output
// Write image to disk imwrite(img, 'output.png'); // Write image to disk imwrite(img
// 4. Enhance contrast img = histeq(img);
// Threshold to create binary image binary = gray_img > 128; // Structuring element (disk of radius 3) se = [0 1 0; 1 1 1; 0 1 0];
// Erosion eroded = imerode(binary, se);