A fuzzy approach to edge level detection

This paper presents a new method for edge level detection. Edge level detection is related to how much attention a person needs to use to detect an edge. The new edge level method is based on the analysis of gradient information of images that is considered as fuzzy information. This fuzzy gradient information is used to determine fuzzy class centroids that define the edge levels. The centroids are obtained with the fuzzy C means algorithm. Once the centroids are defined the gradient information is classified through a distance metric based on the centroids into different edge levels. Results show that this method provides a well-defined methodology to obtain information about edge levels in images that may be used for image analysis purposes. The algorithm also corrects the problems of lost edges and edge level change generated by another edge level algorithm reviewed in this paper.