| 基于并行点火PCNN模型的图像分割新方法 |
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| 引用本文： | 彭真明, 蒋彪, 肖峻, 孟凡斌. 基于并行点火PCNN模型的图像分割新方法. 自动化学报, 2008, 34(9): 1169-1173. doi: 10.3724/SP.J.1004.2008.01169 |
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| 作者姓名： | 彭真明 蒋彪 肖峻 孟凡斌 |
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| 作者单位： | 1.电子科技大学光电信息学院 成都 610054;;2.吉首大学物理科学与信息工程学院 吉首 416000 |
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| 基金项目： | 航空基础科学基金，国防科技预研项目 |
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| 摘 要： | 提出一种并行点火脉冲耦合神经网络(Parallelized firing pulse coupled neural networks, PFPCNN)模型的图像分割方法. 首先用改进的Unit-linking PCNN (ULPCNN)模型对图像进行增强, 便于后续的图像分割. 然后采用PFPCNN新模型对增强后的图像进行分割, 最后用最大香农熵方法判定最佳分割结果. 各种复杂场景下的仿真实验及定量评价表明, 本文提出的图像分割方法, 其效果明显优于常规的PCNN分割方法.
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| 关 键 词： | 脉冲耦合神经网络 并行点火模型 图像增强 最大香农熵 图像分割 |
| 收稿时间： | 2007-06-15 |
| 修稿时间： | 2007-11-12 |
A Novel Method of Image Segmentation Based on Parallelized Firing PCNN |
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| PENG Zhen-Ming, JIANG Biao, XIAO Jun, MENG Fan-Bin. A Novel Method of Image Segmentation Based on Parallelized Firing PCNN. ACTA AUTOMATICA SINICA, 2008, 34(9): 1169-1173. doi: 10.3724/SP.J.1004.2008.01169 |
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| Authors: | PENG Zhen-Ming JIANG Biao XIAO Jun MENG Fan-Bin |
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| Affiliation: | 1. College of Opto-electronic Information, University of Electronic Science and Technology of China, Chengdu, 610054;;;2. College of Physics Science and Information Engineering, Jishou University, Jishou 416000 |
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| Abstract: | A novel method for image segmentation based on parallelized firing pulse coupled neural networks(PFPCNN)is presented in this paper.At first,the improved unit-linking PCNN(ULPCNN)is used to enhance the image.Then,PF- PCNN model is adopted to segment the enhanced image by the improved ULPCNN.Finally,the maximal Shannon entropy is used to determine the optimal result from the segmented im- ages.Experimental results show that the proposed method is more effective than the traditional PCNN and other improved PCNN models by quantitatively evaluating their performance. |
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| Keywords: | Pulse coupled neural networks(PCNN) parallelized firing model image enhancement image segmentation maximum Shannon entropy |
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