ON FEATURE EXTRACTION FOR TEXTURE ANALYSIS

Abstract

Texture analysis has a fundamental importance in image processing and it is widely applied for different fields, e.g. industrial quality control, biomedical imagery, etc. For each texture classification/segmentation problem feature extraction is a crucial task. In this paper we review several methods of feature extraction, such as statistical approaches, transform-based methods and pixel-based structural descriptions. Beside of their princi-ples, advantages and disadvantages occurring during their applications are also described. Theoretical and experimental investigations showed that multichannel texture analysis is an efficient tool and has several advantages with respect to the traditional feature extrac-tion methods. Pixel-based structural features are also presented, which attempt to bridge the gap between statistical and structural feature extraction methods.