Logo image clustering based on advanced statistics

被引:0
作者
Wei, Yi [1 ]
Kamel, Mohamed [2 ]
He, Yiwei [1 ]
机构
[1] Wuhan Univ Technol, Sch Automat, 129 Luoshi Rd, Wuhan 430070, Peoples R China
[2] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
来源
MIPPR 2007: PATTERN RECOGNITION AND COMPUTER VISION | 2007年 / 6788卷
关键词
image clustering; approximation wavelet coefficients; multivariate analysis; maximum likelihood ratio test;
D O I
10.1117/12.750476
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent years, there has been a growing interest in the research of image content description techniques. Among those, image clustering is one of the most frequently discussed topics. Similar to image recognition, image clustering is also a high-level representation technique. However it focuses on the coarse categorization rather than the accurate recognition. Based on wavelet transform (WT) and advanced statistics, the authors propose a novel approach that divides various shaped logo images into groups according to the external boundary of each logo image. Experimental results show that the presented method is accurate, fast and insensitive to defects.
引用
收藏
页数:6
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