Cellular edge detection for color images

Edge is considered an important feature for image processing in computer science. However, to day this technology has mainly be developed for grey scale images as opposed to colored images. Converting to greyscale images involves information loss and is often time consuming. We therefore see a need to develop edge detection for color images as well.In this study we propose a Cellular Edge Detection (CED) algorithm based on Cellular automata (CA) and Cellular Learning Automata (CLA) which is a very accurate and reliable way of edge detecting. Every color edge detection procedure is done via the grayscale rules however there are some noticeable difference. The input image is different when a conversion from RGB to HSV occurs while, in RGB images we propose an average or other way of merging results. Results shows that this new way to find edges work accurately and more efficient. The evaluation of this proposed model calculated by MSE and PSNR

کلیدواژه ها:

CED (Cellular Edge Detection) ، color image edge detection ، CA (Cellular automata) ، CLA (Cellular Learning Automata) ، MSE ، PSNR