Automatic Image Segmentation with PCNN Algorithm Based on Grayscale Correlation

MA Hai-rong; CHENG Xin-wen

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Automatic Image Segmentation with PCNN Algorithm Based on Grayscale Correlation

更新时间：2026-09-04

- Automatic Image Segmentation with PCNN Algorithm Based on Grayscale Correlation
- Vol. 31, Issue 11, Pages: 10-13(2014)
- 作者机构：
  
  中国地质大学(武汉)信息工程学院,湖北,武汉,430074
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
移动端阅览
马海荣, 程新文. 基于灰度相关性的改进PCNN图像自动分割算法[J]. 微电子学与计算机, 2014, 31(11): 10-13.

MA Hai-rong, CHENG Xin-wen. Automatic Image Segmentation with PCNN Algorithm Based on Grayscale Correlation[J]. 2014, 31(11): 10-13.
马海荣, 程新文. 基于灰度相关性的改进PCNN图像自动分割算法[J]. 微电子学与计算机, 2014, 31(11): 10-13. DOI：

MA Hai-rong, CHENG Xin-wen. Automatic Image Segmentation with PCNN Algorithm Based on Grayscale Correlation[J]. 2014, 31(11): 10-13. DOI：

摘要

为了利用脉冲耦合神经网络﹙pulse coupled neural network

PCNN)实现精确的图像自动分割

对PCNN模型进行改进

提出首先根据图像局部灰度相关性和欧氏距离建立连接权矩阵

然后利用最小方差比准则自动判定PCNN的循环次数

实现图像的自动分割

仿真实验结果表明

该方法可实现PCNN算法迭代次数的自动判定

算法适用性强

并可得到较好的分割效果.

Abstract

In order to utilize pulse coupled neural networks (PCNN) for precise automatic image segmentation

in this paper

we improved PCNN model.Firstly

we established a connection weight matrix based on the image local gray correlation and Euclid distance

then

used minimum variance ratio criterion determines cycle times of PCNN automatically

achieved automatic image segmentation.The simulation results showed that this method could determined PCNN number of iterations automatically

and has a strong feasibility and better segmentation results.

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