Image Thresholding Using Cellular Neural Network Combined with Fuzzy C-Means

Thresholding is one of the old, simple, and popular techniques for image segmentation, and has been widely studied. In this paper, an approach for image thresholding based on cellular neural network (CNN) combined with fuzzy c-means (FCM) is presented. The approach realized by threshold CNN (T-CNN), which threshold is obtained automatically via FCM clustering algorithm. Experimental results on real images show that the proposed approach can extract the objects from the background effectively with better visual quality than other methods.