Artificial intelligence algorithms to edges detection of digital images

Edge detection is one of the most important stages in digital image processing, where connected and homogeneous regions are identified based on the gray scale in this study, three approaches were employed to detect edges in various images: the nested design method, the ant colony algorithm, and a proposed method that enhances the ant colony algorithm through nested design. The results varied from one image to another in terms of the of identifying edges, but the three methods are highly efficient in detecting image edges on images of different sizes and gray scale levels, with the superiority of the proposed method based on the statistical criteria PSNR (Peak Signal to Noise Ratio) (image quality) and RMSE (root mean square error). The results of this method were the highest values of PSNR and the lowest values of RMSE, which are the two trade-off criteria.