Implementation of Textile Image Segmentation Using Contextual Clustering and Fuzzy Logic

This paper presents the segmentation analysis on textile images. These images have innumerable textures. The content of the images are regularly arranged or repeated or random in a tessellated fashion. It is not necessary that the entire image has to be compulsorily segmented. However, at least one full object has to be segmented correctly in an image. In this work, a systematic approach has been developed to extract textures from the given texture images. The features of the textile images are extracted and used for segmenting those images using contextual clustering and fuzzy logic. The proposed methods combine to improve the segmentation accuracies and to analyze the effects of parameters of the proposed algorithms in segmentation of textures.