Novel Edge Detection Using BP Neural Network Based on Threshold Binarization

One of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the edge of image where the preciseness and reliability of its results will affect directly the comprehension machine system made for objective world. Several edge detectors have been developed in the past decades, although no single edge detectors have been developed satisfactorily enough for all application. In this paper, a new edge detection technique is proposed basis on the BP neural network. Here, it is classified the edge patterns of binary images into 16 possible types of visual patterns. In the following, After training the pre-defined edge patterns, the BP neural network is applied to correspond any type of edges with its related visual pattern. The results demonstrated that the new proposed technique provides the better results compared with traditional edge detection techniques while improved the computations complexity.