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).

引用

页码：367 / 372

页数：6

共 17 条

[11] Kasprzak M., 1996, Proceedings of the 13th International Conference on Pattern Recognition, P394, DOI 10.1109/ICPR.1996.546855
[12] Kasprzak W., PRACE NAUKOWE ELEKT
[13] Filtering for texture classification: A comparative study
Randen, T
Husoy, JH
[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1999, 21 (04) : 291 - 310
[14] Skarbek W., 1993, METODY REPREZENTACJI, V6
[15] Using discriminant eigenfeatures for image retrieval
Swets, DL
Weng, JJ
[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1996, 18 (08) : 831 - 836
[16] EIGENFACES FOR RECOGNITION
TURK, M
PENTLAND, A
[J]. JOURNAL OF COGNITIVE NEUROSCIENCE, 1991, 3 (01) : 71 - 86
[17] TURNER MR, 1986, BIOL CYBERN, V55, P71

← 1 2 →