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All textile industries aim to produce competitive materials and the competi tion enhancement depends mainly on designs and quality of the dresses produced by each industry. Every day, a vast amount of textile images are being generated such as images of shirts, jeans, t -shirts and sarees. A principal driver of innovation is WorldWide Web, unleashing publication at the scale of tens and millions of content creators. Images play an important role as a picture is worth thousand words in the field of textile design and marketing. A retrieving of images needs special concepts such as i mage annotation, context, and image content and image values. This research work aimed at studying the image mining process in detail and analyzes the methods for retrieval. The textile images analyze various methods for clustering the images and developing an algorithm for the same. The retrieval method considered is based on relevance feedback, scalable method, edge histogram and color layout. The image clustering algorithm is designed based on color descriptors and k -means clustering algorithm. A softwar e prototype to prove the proposed algorithm has been developed using net beans integrated development environment and found successful.

Design and Development of an Algorithm for Image Clustering In Textile Image Retrieval Using Color Descriptors