Independent Component Analysis of Textures

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).

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: Roberto Manduchi, Javier Portilla
• Keywords: Base Functions, Blind Signal Processing, Computer Vision, ICCV 1999, Independent Component Analysis, Texture Feature Detection, Universal Gabor Functions