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Noise Robust Image Edge Detection based upon the Automatic Anisotropic Gaussian Kernels

Zhang, W.; Zhao, Y.; Breckon, T.P.; Chen, L.

Noise Robust Image Edge Detection based upon the Automatic Anisotropic Gaussian Kernels Thumbnail


Authors

W. Zhang

Y. Zhao

L. Chen



Abstract

This paper presents a novel noise robust edge detector based upon the automatic anisotropic Gaussian kernels (ANGKs), which also addresses the current problem that the seminal Canny edge detector may miss some obvious crossing edge details. Firstly, automatic ANGKs are designed according to the noise suppression, edge resolution and localization precision, which also conciliate the conflict between them. Secondly, reasons why cross-edge points are missing from Canny detector results using isotropic Gaussian kernel are analyzed. Thirdly, the automatic ANGKs are used to smooth image and a revised edge extraction method is used to extract edges. Finally, the aggregate test receiver-operating-characteristic (ROC) curves and Pratt's Figure of Merit (FOM) are used to evaluate the proposed detector against state-of-the-art edge detectors. The experiment results show that the proposed algorithm can obtain better performance for noise-free and noisy images.

Citation

Zhang, W., Zhao, Y., Breckon, T., & Chen, L. (2016). Noise Robust Image Edge Detection based upon the Automatic Anisotropic Gaussian Kernels. Pattern Recognition, 63(8), 193-205. https://doi.org/10.1016/j.patcog.2016.10.008

Journal Article Type Article
Acceptance Date Oct 5, 2016
Online Publication Date Oct 6, 2016
Publication Date Oct 6, 2016
Deposit Date Jan 10, 2017
Publicly Available Date Oct 6, 2017
Journal Pattern Recognition
Print ISSN 0031-3203
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 63
Issue 8
Pages 193-205
DOI https://doi.org/10.1016/j.patcog.2016.10.008
Public URL https://durham-repository.worktribe.com/output/1388872
Related Public URLs http://community.dur.ac.uk/toby.breckon/publications/papers/zhang17edges.pdf

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