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An Adaptive Algorithm for Grey Image Edge Detection Based on Grey Correlation Analysis

机译:基于灰度相关分析的自适应灰度图像边缘检测算法

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In the original algorithm for grey correlation analysis, the detected edge is comparatively rough and the thresholds need determining in advance. Thus, an adaptive edge detection method based on grey correlation analysis is proposed, in which the basic principle of the original algorithm for grey correlation analysis is used to get adaptively automatic threshold according to the mean value of the 3×3 area pixels around the detecting pixel and the property of people's vision. Because the false edge that the proposed algorithm detected is relatively large, the proposed algorithm is enhanced by dealing with the eight neighboring pixels around the edge pixel, which is merged to get the final edge map. The experimental results show that the algorithm can get more complete edge map with better continuity by comparing with the traditional edge detection algorithms.
机译:在用于灰度相关分析的原始算法中,检测到的边缘相对较粗糙,需要预先确定阈值。因此,提出了一种基于灰度相关分析的自适应边缘检测方法,该方法利用原始灰度相关分析算法的基本原理,根据检测周围3×3面积像素的平均值,自适应地得到自动阈值。像素和人们视野的属性。由于该算法检测到的虚假边缘较大,因此通过处理边缘像素周围的八个相邻像素对算法进行增强,合并后得到最终的边缘图。实验结果表明,与传统的边缘检测算法相比,该算法可以获得更完整的边缘图,具有更好的连续性。

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