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基于灰度共生矩阵和BP神经网络集成的纹理图像分类
引用本文:马帅营.基于灰度共生矩阵和BP神经网络集成的纹理图像分类[J].大连民族学院学报,2009,11(3):260-263.
作者姓名:马帅营
作者单位:大连民族学院,现代教育技术中心,辽宁,大连,116605
摘    要:通过对灰度共生矩阵的分析,提取图像的纹理特征参数,并用BP神经网络集成的方法对Brodatz纹理库图像进行分类,仿真结果显示,其分类效果优于单一的BP神经网络,可有效提高分类识别率。

关 键 词:纹理  灰度共生矩阵  BP神经网络  神经网络集成  图像分类

Texture Image Classification Based on Gray Level Co-occurrence Matrix and BP Neural Network Ensemble
MA Shuai-Ying.Texture Image Classification Based on Gray Level Co-occurrence Matrix and BP Neural Network Ensemble[J].Journal of Dalian Nationalities University,2009,11(3):260-263.
Authors:MA Shuai-Ying
Institution:MA Shuai-Ying(Modern Educational Technology Center,Dalian Nationalities University,Dalian Liaoning 116605,China)
Abstract:This paper investigates the collection of textural parameters according to the analysis of grey level co-occurrence matrix and classification of Brodatz texture database by means of BP neural network ensemble.The emulation result shows that the classification effect is superior than that from simple BP neural network,the classification discrimination is increased effectively.
Keywords:texture  grey level co-occurrence matrix  BP neural network  neural network ensemble  image classification  
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