Image texture classification based on wavelet transform and SVM

被引：0
|
作者：
Lan, Gao [1 ]
Song Qingguo [1 ]
Chuang, Li
Qing, Hua
Chuang, Yang
机构：
[1] Wuhan Univ Technol, Sch Energy & Power Engn, Wuhan, Peoples R China
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE INFORMATION COMPUTING AND AUTOMATION, VOLS 1-3 | 2008年
关键词：
wavelet transform (WT); image texture support vector machines (SVM); parameter select;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Wavelet transform (WT) has the advantage of multi-scale analysis, which is especially fit for classifying image texture. Since the appearance of Mallat pyramidal algorithm ([1]), WT has been widely used. In this paper, texture feature vector are extracted and calculated by wavelet transform, and then, we use SVM as the classifier, in which we bring out a novel method - Bayesian and cross-validation to select the parameter, and establish the SVM model. With the experiment result, the method is proved effective in image texture classification.
引用
收藏
页码：834 / +
页数：2
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