Based On The The Canny Theory Of Adaptive Edge Detection Method Study

The edge is an important feature that human vision recognizes image target. Edge is also one of the most fundamental character of a image. Edge detection is one of the most important studying projects in image processing and computer vision. It is a hot point for researchers in the field of image measurement technology. On the basis of analyzing the existing methods of edge detection,this paper proposes an Canny adaptive method according to the requirement of edge detection in image measurement, Its main content is as follows:1 .This paper introduces some classic methods, The basic concepts of these methods are summarized. These image edge detection methods are analyzed experimentally. The advantages and disadvantages are also analyzed.2. Canny criteria and Canny edge detection algorithm are analyzed in details.3. Based on Canny algorithm and anisotropic nonlinear diffusion filtering , an adaptive Canny edge detection method is proposed in this paper. This method not only keeps the excellent performance of Canny operator in good localization , only one response to a single edge and good detection, but also improves the performance in the detail edge detection and in restraining false edge. In this method, A probability theory based model for image gradient classification is established and then application of it to determinate the thresholds for Canny operator automatically. It improves the automaticity of edge detection.4.The concrete realization of the Canny adaptive method is introduced in this paper. Through experiment and test result analysis, it demonstrates that the Canny adaptive edge detection method is an efficient approach on edge detection.An effective method is provided for the practical image measurement.