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Proceedings Paper • new

Image segmentation algorithm based on improved PCNN
Author(s): Hong Chen; Chengdong Wu; Xiaosheng Yu; Jiahui Wu
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Paper Abstract

A modified simplified Pulse Coupled Neural Network (PCNN) model is proposed in this article based on simplified PCNN. Some work have done to enrich this model, such as imposing restrictions items of the inputs, improving linking inputs and internal activity of PCNN. A self-adaptive parameter setting method of linking coefficient and threshold value decay time constant is proposed here, too. At last, we realized image segmentation algorithm for five pictures based on this proposed simplified PCNN model and PSO. Experimental results demonstrate that this image segmentation algorithm is much better than method of SPCNN and OTSU.

Paper Details

Date Published: 15 November 2017
PDF: 6 pages
Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060528 (15 November 2017); doi: 10.1117/12.2292798
Show Author Affiliations
Hong Chen, Northeastern Univ. (China)
Anshan Normal Univ. (China)
Chengdong Wu, Northeastern Univ. (China)
Xiaosheng Yu, Northeastern Univ. (China)
Jiahui Wu, Northeastern Univ. (China)


Published in SPIE Proceedings Vol. 10605:
LIDAR Imaging Detection and Target Recognition 2017
Yueguang Lv; Weimin Bao; Weibiao Chen; Zelin Shi; Jianzhong Su; Jindong Fei; Wei Gong; Shensheng Han; Weiqi Jin; Jian Yang, Editor(s)

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