关键词: 边缘检测, 多尺度, 多分辨率, 可变局部边缘模式, 加权融合

Abstract: Because traditional square-shaped edge detectors based on gradient only contain few directions （generally 2 or 4）, edges are not detected from multi-resolution point of view. Therefore so much edge information from other directions is lost. Aiming at the above problem, an edge descriptor, called Varied Local Edge Pattern （VLEP）, with multi-scale and multi-resolution properties is proposed, and is applied to edge detection. Main idea about this method involves that image is firstly smoothed by Gaussian filter. Then one or more groups of VLEP descriptors are convolved with the processed image, and edge intensity and edge gradient value are obtained. Finally edges are extracted by adaptable gradient thresholds and binaryzation. In addition, weighted fusion idea is considered when multiple groups of VLEP descriptors are used, so that richer edge information is obtained. Experimental results show that the proposed edge detection method achieves better performance than other state-of-the-art edge detection methods.

Key words: edge detection, multi-scale, multi-resolution, Varied Local Edge Pattern （VLEP）, weighted fusion