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Proceedings Paper

A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model
Author(s): Kun Gao; Hu Yang; Xiaomei Chen; Guoqiang Ni
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Paper Abstract

Because of complex thermal objects in an infrared image, the prevalent image edge detection operators are often suitable for a certain scene and extract too wide edges sometimes. From a biological point of view, the image edge detection operators work reliably when assuming a convolution-based receptive field architecture. A DoG (Difference-of- Gaussians) model filter based on ON-center retinal ganglion cell receptive field architecture with artificial eye tremors introduced is proposed for the image contour detection. Aiming at the blurred edges of an infrared image, the subsequent orthogonal polynomial interpolation and sub-pixel level edge detection in rough edge pixel neighborhood is adopted to locate the foregoing rough edges in sub-pixel level. Numerical simulations show that this method can locate the target edge accurately and robustly.

Paper Details

Date Published: 8 January 2008
PDF: 11 pages
Proc. SPIE 6835, Infrared Materials, Devices, and Applications, 68351Y (8 January 2008); doi: 10.1117/12.758162
Show Author Affiliations
Kun Gao, Beijing Institute of Technology (China)
Hu Yang, Beijing Institute of Technology (China)
Xiaomei Chen, Beijing Institute of Technology (China)
Guoqiang Ni, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 6835:
Infrared Materials, Devices, and Applications
Yi Cai; Haimei Gong; Jean-Pierre Chatard, Editor(s)

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