A soft image edge detection approach based on the time matrix of a PCNN

Image segmentation has attracted the attention of researcher for many decades. Different approaches have been developed in order to find the solution in many different segmentation situations. In this paper we propose a novel edge detection approach aimed to generate useful information to achieve segmentation. The proposed method is based on analysis of the information provided by the time matrix generated from a pulse coupled neural network, PCNN. This information represents gray level differences among the pixel images. Two different schemes for edge detection are presented. The first scheme is developed to generate edges from coarse images and the second one to deal with more detailed edges. Similarity of this method with a previous developed method based on fuzzy edge level detection is also covered in the paper. Final results show that the proposed method may be used as a new alternative to define image edges of different levels for further analysis.