Image segmentation algorithm based on improved PCNN

Hong Chen; Chengdong Wu; Xiaosheng Yu; Jiahui Wu

doi:10.1117/12.2292798

15 November 2017 Image segmentation algorithm based on improved PCNN

Hong Chen, Chengdong Wu, Xiaosheng Yu, Jiahui Wu

Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 1060528 (2017) https://doi.org/10.1117/12.2292798
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China

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.

Citation Download Citation

Hong Chen, Chengdong Wu, Xiaosheng Yu, and Jiahui Wu "Image segmentation algorithm based on improved PCNN", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060528 (15 November 2017); https://doi.org/10.1117/12.2292798

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