21 July 2017 An image edge detection based on the orientation response mechanisms of an integrate-and-fire neurons model
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042010 (2017) https://doi.org/10.1117/12.2282547
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
Abstract
Considering that traditional image edge detection methods can’t reflect the orientation selection characteristics of a human visual perception system and the firing mechanism of neuron spikes, a new method of image edge detection based on orientation response mechanisms of an integrate-and-fire (IF) neurons model are presented in this paper. To fully reflect orientation selection characteristics of the human visual system, the Log-Gabor orientation response model is applied for image orientation preprocessing. The spikes sequence fired by IF neurons model is used for image edge detection. The results of various experiments show that our method can truly reflect the biological characteristics. By comparison with the traditional image edge detection methods, our method is focused on the fine details preservation, and can highlight image edge.
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Hongxia Ni, Wei Wu, "An image edge detection based on the orientation response mechanisms of an integrate-and-fire neurons model", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042010 (21 July 2017); doi: 10.1117/12.2282547; https://doi.org/10.1117/12.2282547
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