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A novel approach for edge detection based on the theory of universal gravity

机译:基于万有引力理论的边缘检测新方法

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摘要

This paper presents a new, simple and effective low-level processing edge detection algorithm based on the law of universal gravity. The algorithm assumes that each image pixel is a celestial body with a mass represented by its grayscale intensity. Accordingly, each celestial body exerts forces onto its neighboring pixels and in return receives forces from the neighboring pixels. These forces can be calculated by the law of universal gravity. The vector sums of all gravitational forces along, respectively, the horizontal and the vertical directions are used to compute the magnitude and the direction of signal variations. Edges are characterized by high magnitude of gravitational forces along a particular direction and can therefore be detected. The proposed algorithm was tested and compared with conventional methods such as Sobel, LOG, and Canny using several standard images, with and without the contamination of Gaussian white noise and salt & pepper noise. Results show that the proposed edge detector is more robust under noisy conditions. Furthermore, the edge detector can be tuned to work at any desired scale. (c) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
机译:本文提出了一种基于万有引力定律的新的,简单有效的低层处理边缘检测算法。该算法假定每个图像像素都是一个天体,其质量由其灰度强度表示。因此,每个天体在其相邻像素上施加力,并且反过来从相邻像素接收力。这些力可以通过万有引力定律来计算。分别沿水平方向和垂直方向的所有重力的矢量和用于计算信号变化的大小和方向。边缘的特征是沿特定方向的重力很大,因此可以检测到。使用几种标准图像对提出的算法进行了测试,并与诸如Sobel,LOG和Canny的常规方法进行了比较,并带有或不带有高斯白噪声,盐和胡椒噪声的污染。结果表明,所提出的边缘检测器在嘈杂的条件下更为鲁棒。此外,可以将边缘检测器调整为以任何所需的比例工作。 (c)2007模式识别学会。由Elsevier Ltd.出版。保留所有权利。

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