Certain investigations on texture analysis using wavelet based laws approaches and their applications

Abstract

One of the fundamental issues in image processing and machine vision is texture analysis Texture analysis is a process that consists of texture feature extraction classification and segmentation The present work is concerned with the analysis of texture images along with few applications Multi resolution signal processing methods higher order statistics based schemes and computationally low cost texture analysis approaches are investigated Wavelet transform has been widely used for texture classification Wavelet transform uses patial frequency information of texture which is required for classification and segmentation Consequently these advantages are combined to form novel algorithms Laws texture energy measure features have been used for texture analysis The present work mainly concerns with Wavelet based Laws approach where the Wavelet transform and Laws masks are combined to increase the texture classification performance and segmentation efficiency