Image segmentation using continuous cellular automata

Image segmentation is still one of nowadays problems in image processing, in which there is no ideal or optimal solution due to the large variety of images, their characteristics, and the type of information we try to extract. In this paper, we are proposing a new method of segmentation which is an edge detector based on continuous cellular automaton for both black and white images and grayscale images. This new method presents the advantage of facilitating the evolution of cellular automata until the final configuration, without the tedious process of searching manually the rules set which leads to the desired result.