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An Efficient Content Based Image Retrieval System for Color and Shape Using Optimized K-Means Algorithm


A.Komali, R.Veera Babu, D.Sunil Kumar, K.Ganapathi Babu


Vol. 15  No. 4  pp. 127-131


This paper deals with the Content Based Image Retrieval CBIR system which is the challenging research platform in the digital image processing. The important theme of using CBIR is to extract visual content of an image automatically, like color, texture, or shape. The simple process to retrieve an image from the image set, we use image search tools like Google images, Yahoo, etc. The main goal of view is based on the efficient search on information set. In the point of searching text, we can search flexibly by using keywords, but if we use images, we search using some features of images, and these features are the keywords. Color and shape image retrieval (CSIR) describes a possible solution for designing and implementing a project which can handle the informational gap between a color and shape of an image. This similar color and shape of an image is retrieved by comparing number of images in datasets. This CSIR can be developed by using K-Means algorithm for getting retrieval results of similar image efficiently. By using K-Means algorithm, more number of iterations occurred. In order to reduce the number of iterations we use codebook algorithm. This CSIR can be used in several applications such as photo sharing sites, forensic lab, etc. CLARANS is the normal method which is used to reduce the bugs occurred in the existing algorithms


K-Means Algorithm, code book algorithm, CLARANS.