An analytical review of texture feature extraction approaches

Abstract

Image registration has been an essential task in computer vision and image processing. There are many applications of image registration, for instance, in medical systems. Image registration consists of four main steps, including Features Extraction, Feature Matching, Transform Model Estimation, Resampling and Transformation. The Feature Extraction step makes the image registration process more accurate. Despite a large number of survey articles on texture feature extraction approaches, a comprehensive classification of approaches is still required, which also identifies the strengths and weaknesses of each approach. Therefore, the novelty of this paper, our analytical framework includes three major components: a complete classification of texture feature extraction approaches, using crucial evaluation criteria to present an analytical and qualitative comparison between each approach, which simplifies the accurate selection of the proposed approaches for the intended application. Our framework can also lead to the development of texture feature extraction approaches in future research of scientists.