摘要
论述了基于滤波器组的纹理分类方法。该方法首先利用滤波器组对纹理进行滤波,纹理特征是用滤波器输出的统计值表示的;然后用这些特征向量进行纹理分类研究,分类主要利用了简单(naive)Bayes分类方法和最大加权相关树分类方法。实验显示,最大加权相关树分类方法的效果是较好的。
The objective of this paper is the classification of textured materials unifying filter approach. Firstly, the filter bank is exploited to generate features, and the filter responses are described as the feature of texture. Secondly, the two classification approaches： the maximum weight dependance trees and the naive hayes classification are explored. Finally, the experiments demonstrated that the method of maximum weight dependence trees （MWDT） has a better result. And MWDT can be a powerful tool for texture classification.
出处
《计算机技术与发展》
2007年第9期78-81,共4页
Computer Technology and Development
基金
科技部重大基础项目基金资助(国科基字[2001(51)])
关键词
纹理
机器学习
分类
texture
machine learning
classification
