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Proceedings Paper

Edge detection based on adaptive oriented double opponent neurons
Author(s): Zhen Zhang; Huiqi Li; Guoru Zhao
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Paper Abstract

A new method of edge detection based on adaptive oriented double opponent neurons is presented in this paper, considering that the homocentric opponent receptive field is lack of directionality, and the anisotropic of receptive field in ODOG model will be badly restrained during weighting process. To get relatively complete image edges, the edge directional operators are introduced to choose Difference of Gaussians (DOG) model or the orientations of Oriented Difference of Gaussians (ODOG) model automatically. Compared with DOG and ODOG methods, the methods detect weak edges effectively with better edge connectivity and edge confidence.

Paper Details

Date Published: 9 August 2018
PDF: 5 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108062Z (9 August 2018); doi: 10.1117/12.2503370
Show Author Affiliations
Zhen Zhang, Wuhan Univ. of Technology (China)
Huiqi Li, Shenzhen Institutes of Advanced Technology (China)
Guoru Zhao, Shenzhen Institutes of Advanced Technology (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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