Image edge detection based on singular value feature vector and gradient operator

1.
College of Computer Engineering, Jiangsu University of Technology, Changzhou 213001, China
2.
School of Foreign Languages, Jiangsu University of Technology, Changzhou 213001, China
3.
School of Computer Engineering, Nanjing Institute of Technology, Nanjing 211167, China
4.
Nanjing Vivo Software Technology Co., Ltd., Nanjing 211106, China
5.
Department of Computer Science, King Saud University, Riyadh 11362, Saudi Arabia

Received: 18 March 2020 Accepted: 18 May 2020 Published: 22 May 2020

Abstract
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This paper presents an edge detection algorithm based on singular value eigenvector and gradient operator. In the proposed algorithm, the singular values of image blocks are first calculated, and the Sobel gradient template is extended to eight other directions. Then the gradient values of image pixels are determined according to the stability of the singular values of image blocks. The determination of gradient threshold is considered from both global and local aspects. After calculating the global and local gradient thresholds of the original image, the gradient threshold of the whole image is determined by weighting function. Then the edge pixels of the image are filtered according to the gradient threshold, and the edge information image of the original image is obtained. The experimental data show that the proposed algorithm can resist a certain degree of noise interference, and the accuracy and efficiency of edge extraction are better than other similar algorithms.
- singular value feature vector,
- gradient operator,
- edge detection
Citation: Jiali Tang, Yan Wang, Chenrong Huang, Huangxiaolie Liu, Najla Al-Nabhan. Image edge detection based on singular value feature vector and gradient operator[J]. Mathematical Biosciences and Engineering, 2020, 17(4): 3721-3735. doi: 10.3934/mbe.2020209

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Abstract

This paper presents an edge detection algorithm based on singular value eigenvector and gradient operator. In the proposed algorithm, the singular values of image blocks are first calculated, and the Sobel gradient template is extended to eight other directions. Then the gradient values of image pixels are determined according to the stability of the singular values of image blocks. The determination of gradient threshold is considered from both global and local aspects. After calculating the global and local gradient thresholds of the original image, the gradient threshold of the whole image is determined by weighting function. Then the edge pixels of the image are filtered according to the gradient threshold, and the edge information image of the original image is obtained. The experimental data show that the proposed algorithm can resist a certain degree of noise interference, and the accuracy and efficiency of edge extraction are better than other similar algorithms.

References

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