SURVEY AND DESIGN OF CONTENT BASED IMAGE RETRIEVAL USING DATA MINING CLUSTERING ALGORITHM

As processors become increasingly powerful, and memories become increasingly cheaper, the deployment of large image databases for a variety of applications have now become realizable. Databases of art works, satellite and medical imagery have been attracting more and more users in various professional fields for example, geography, medicine, architecture, advertising, design, fashion, and publishing. Effectively accessing desired images from large and varied image databases is now a necessity. Due to development of multimedia technology and increasing vogue of the computer network, the conventional information retrieval systems are not able to overcome the users' current need. There are various areas in which digital images are used such ascrime prevention, commerce, finger print recognition, surveillance, hospitals, engineering, architecture, fashion, graphic design, academics, historical research, and government institutions etc. Because of this widespread demand we need to enhance in retrieval precision and minimized retrieval time. The prior methods were only dependent on text based searching instead of its visual feature. Many times just one keyword is redundantly used with more than one images, therefore it leads to erroneous outcomes. Consequently, Content Based Image Retrieval (CBIR) is evolved to defeat the restriction of text based retrieval. Problems which we are identified in the existing image retrieval systems are as follows- How to retrieve the search image accurately, how we can manage a large database of images, how we can make the searching process efficient. In this paper, we will study different content based image retrieval algorithms and provide a way through which we can provide efficient access to image data