A method for edge detection in gray level images, based on cellular neural networks

Edge detection is an important preprocessing task in artificial vision systems. In this paper the utility of a recently reported CNN template for edge detection was verified over a set of black and white images. These images were obtained applying an threshold procedure to their corresponding associated gray level images. An optimal threshold value for preserving a large number of features from the original gray level input images was used. Combining the threshold and edge detection templates, a procedure to obtain edges on gray level images was implemented.