INDEPENDENT COMPONENT ANALYSIS OF TEXTURES IN ANGIOGRAPHY IMAGES

被引：3
作者：
Snitkowska, Ewa [1 ]
Kasprzak, Wlodzimierz [1 ]
机构：
[1] Warsaw Univ Technol, Inst Control & Computat Engn, Ul Nowowiejska 15-19, PL-00665 Warsaw, Poland
来源：
COMPUTER VISION AND GRAPHICS (ICCVG 2004) | 2006年 / 32卷
关键词：
feature detection; texture classification; independent component analysis;
D O I：
10.1007/1-4020-4179-9_53
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The technique of independent component analysis (ICA) is applied for texture feature detection. In ICA an optimal transformation (with respect to the statistical structure of the image samples set) is discovered via blind signal processing. Any texture is considered as a mixture of independent sources (basic functions of detected transformation). Experimental comparison is documented on the compactness and separability of base functions, the data-specific ICA-based and universal Gabor functions (the latter are set by default for all kinds of images).
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收藏
页码：367 / 372
页数：6
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