ADAPTIVE TEXTURE IMAGE ANALYSIS USING FOREGROUND AND BACKGROUND CLUSTERING TECHNIQUES

Abstract

Texture analysis is a pivotal area in computer vision and image processing with applications spanning from image classification to medical imaging. In this paper, we propose a novel approach for adaptive texture image analysis by leveraging foreground and background clustering techniques. The conventional texture analysis methods often face challenges in handling complex scenes with varying textures and uneven illumination conditions. Our proposed method addresses these challenges by dynamically segmenting images into foreground and background regions, allowing for more effective texture analysis.