Improved pulse-coupled neural network for target segmentation in infrared images

Xiangwei Kong; Jing Huang; Hao Shi

doi:10.1117/12.441693

20 September 2001 Improved pulse-coupled neural network for target segmentation in infrared images

Xiangwei Kong, Jing Huang, Hao Shi

Proceedings Volume 4555, Neural Network and Distributed Processing; (2001) https://doi.org/10.1117/12.441693
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

This paper presents a new image segmentation algorithm based on the pulse coupled neural network (PCNN) and histogram method for infrared images. The proposed algorithm abandons entirely the mechanism of the time exponential decaying function and uses the results of the gray-level histogram analysis as the interior thresholds of PCNN, meanwhile, it keeps the advantage of briding small spatial gaps and minor intensity variations. Experiment results demonstrate that the proposed algorithm can get more complete region and edge information in infrared images. It is also of much lower complexity and of high speed than the original one.

Citation Download Citation

Xiangwei Kong, Jing Huang, and Hao Shi "Improved pulse-coupled neural network for target segmentation in infrared images", Proc. SPIE 4555, Neural Network and Distributed Processing, (20 September 2001); https://doi.org/10.1117/12.441693

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