A new approach to image segmentation based on simplified region growing PCNN
A new approach to image segmentation based on simplified region growing PCNN
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基于简化区域生长PCNN的图像分割新方法
DOI：
10.1016/j.amc.2008.05.029
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发表时间：
2008-11-15
影响因子：
4
通讯作者：
Jia, Ruixin
中科院分区：
文献类型：
--
作者：
Lu, Yunfeng;Miao, Jun;Jia, Ruixin
区域生长脉冲耦合神经网络(PCNN)算法是一种有效的多值图像分割方法。然而，作为PCNN模型的一种，选择合适的参数通常是困难的。本文提出了一种通过修改连接通道函数来改进区域生长PCNN模型的新方法，降低了参数调整的复杂度。当处理不同区域之间的边缘像素时，区域生长PCNN是不有效的，因为边缘像素和中心像素被不公平地处理。为了克服这一缺点，该方法通过将边缘像素和中心像素设置为接收相同的链接输入来处理边缘像素，如果它们处于相似的条件下。计算机仿真结果表明，该算法能有效地处理边缘像素，并能得到清晰的区域边界。(C)2008 Elsevier Inc.保留所有权利。
The region growing pulse coupled neural network (PCNN) algorithm is an efficient method for multi-value image segmentation. However, as a kind of PCNN models, choosing appropriate parameters are usually difficult. This paper brings forward a new approach which improves the region growing PCNN model by modifying the linking channel function and decreases the complexity of adjusting parameters. The region growing PCNN is not effective when processing the edge pixels between different regions because the edge pixels and central pixels are dealt with unfairly. In order to overcome this disadvantage, the proposed method processes the edge pixels by setting the edge pixels and central pixels to receive same linking input if they are in similar condition. Computer simulations prove it can process the edge pixels efficiently and obtain clear boundaries between different regions. (C) 2008 Elsevier Inc. All rights reserved.