Paper
19 February 2018 Improved CORF model of simple cell combined with non-classical receptive field and its application on edge detection
Xiao Sun, Guobei Chai, Wei Liu, Wenzhuo Bao, Xiaoning Zhao, Delie Ming
Author Affiliations +
Proceedings Volume 10608, MIPPR 2017: Automatic Target Recognition and Navigation; 106080R (2018) https://doi.org/10.1117/12.2288742
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
Simple cells in primary visual cortex are believed to extract local edge information from a visual scene. In this paper, inspired by different receptive field properties and visual information flow paths of neurons, an improved Combination of Receptive Fields (CORF) model combined with non-classical receptive fields was proposed to simulate the responses of simple cell’s receptive fields. Compared to the classical model, the proposed model is able to better imitate simple cell’s physiologic structure with consideration of facilitation and suppression of non-classical receptive fields. And on this base, an edge detection algorithm as an application of the improved CORF model was proposed. Experimental results validate the robustness of the proposed algorithm to noise and background interference.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiao Sun, Guobei Chai, Wei Liu, Wenzhuo Bao, Xiaoning Zhao, and Delie Ming "Improved CORF model of simple cell combined with non-classical receptive field and its application on edge detection", Proc. SPIE 10608, MIPPR 2017: Automatic Target Recognition and Navigation, 106080R (19 February 2018); https://doi.org/10.1117/12.2288742
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KEYWORDS
Visual process modeling

Edge detection

Visualization

Data modeling

Neurons

Performance modeling

Information visualization

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