基于特征提取和BP神经网络的纹理分类算法

Tongyang Liu, Zongguo Liu, Guoqing Wu
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摘要

本文将自然语言的织构概念应用到织构分类中,将自然织构分为十类。在此基础上,我们找到了一个小的自然纹理图库。本文讨论了纹理特征提取的常用方法,提出了Gabor滤波器的具体算法。为了保证特征提取的有效性,我们采用BP网络作为分类器进行实验,取得了满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Algorithm of Texture Classification Based on Feature Extraction and BP Neural Network
In this paper, we apply the texture conception of natural language to the texture classiflcation, and classify the natural texture into ten classes. Basing on the above, we found a small image library of natural texture. In the thesis, we discuss the common means of texture feature extraction, and bring forward a speciflc algorithm for Gabor fllter. In order to validity of the feature extraction, we adopt the BP network as the classifler to carry out our experiments, which bring us satisfying results.
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