Research On Algorithm Of Multiscale Adaptive Edge Detection

Edge detection is the base of the image measuring, image segmentation, image compressing and pattern recognition and so on. Edge detection is one of the important subjects in the field of computer vision and image measuring. How to detect the edge of object exactly and quickly is a researchful holspot of image processing.Some classic methods and efficient edge-detection methods are introduced in this paper. The basic concepts of these techniques are summarized and the methods' advantages and disadvantages are analyzed.Multiscale adaptive filtering is particularly discussed in this paper. Multiscale adaptive Gauss filtering is proposed. This method estimates the scale of edge based on local gray scale statistic. The basic theory and the concrete algorithm of the multiscale adaptive Gauss filtering are summarized and some improvements are made.Based on Canny theory and multiscale adaptive Gauss filtering, an adaptive Canny edge-detection method is proposed in this paper. This method not only keeps the cxcellent 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 good detection. Canny adaptive method detects the edges with adaptive threshold value according to the gradient information. That improves the automaticity of edge-detection. The theories and the concrete algorithm of the Canny adaptive method are introduced in this paper. With the mathematic analysis and test result, it demonstrates that the Canny adaptive edge-detection method is a valid method on edge-detection.Using the multiscale adaptive Gauss filtering method and the Canny adaptive method, a experiment is designed to orientate the surveyor's board, extract the exact edges and the center coordinate figures of the surveyor points. With the mathematic analysis and lots of experiments, it demonstrates that using the method proposed in this paper can quickly and exactly detect the edge of object in different scales.