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Image Edge Detection Based on Relative Degree of Grey Incidence and Sobel Operator

机译:基于灰关联度和Sobel算子的图像边缘检测

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摘要

Edge points are characterized by sharp transitions in gray levels in adjacent pixels, and relative degree of grey incidence can just reflect the degree of variations. In this paper an image edge detection method integrating relative degree of grey incidence with Sobel operator is presented. Firstly, the comparison sequence is constructed by sequentially ranking a certain pixel and its eight neighborhood of the image, and the reference sequence is formed by taking two orientation operator of Sobel operator. Secondly, the quantitative level difference between reference sequence and behavior sequence is decreased using initialization operation. Then the pixel concerned can be judged as an edge point when there exists a higher relative degree of grey incidence, which means similar geometric shapes of two sequences. By comparing the experimental results, it is proved that the strategy proposed in this paper can detect more details many traditional methods can not find.
机译:边缘点的特征在于相邻像素中的灰度级急剧过渡,并且相对的灰度入射程度可以反映变化的程度。本文提出了一种结合边缘相对灰度与Sobel算子的图像边缘检测方法。首先,比较序列是通过对图像的某个像素及其八个邻域进行顺序排序而构造的,而参考序列是通过采用Sobel算子的两个方向算子形成的。其次,使用初始化操作减小了参考序列和行为序列之间的定量水平差。然后,当存在相对较高的灰度入射度时,可以将相关像素判断为边缘点,这意味着两个序列的几何形状相似。通过比较实验结果,证明了本文提出的策略可以检测到许多传统方法找不到的更多细节。

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