Hybrid Feature Selection Based Machine Learning Approaches for Texture Classification
The classification process is an important task in many applications of computer image analysis for classifying images based on color or texture low-level features. Quantitative study of images is often concerned with four types of parameters, which are of fundamental importance. These are contrast, which determines the quality of an image, colour, which adds more useful discriminatory information to the image, shape, which recognizes the various objects contained in an image, and texture, which describes the spatial distribution of tonal value within band and provide useful information for performing automatic interpretation and recognition. Texture classification assigns a given texture to some texture classes.