A method of edge detection combined by discrete information entropy and self-organizing map

An edge detection method by combining image entropy and Self -Organizing Map (SOM) is proposed in this paper. First, discrete information entropy is used to curve up the smooth region and the region of gray level abruptly changed. This can decrease the latter process. Then we transform the gray level image to ideal binary pattern of pixels. We define six classes' edge and six edge prototype vectors. These edge prototype vectors are fed into input layer of the Self -Organizing Map (SOM). Classifying the type of edge through this network, the edge image is obtained. At last, the speckle edges are discarded from the edge image. Experimental results show that it gained better edge image compared with other edge detection methods.