AN EFFICIENT/ENHANCED CONTENT BASED IMAGE RETRIEVAL FOR A COMPUTATIONAL ENGINE

A picture or image is worth a thousand words. It is very much pertinent to the field of image processing. In the recent years, much advancement in VLSI technologies has triggered the abundant availability of powerful processors in the market. With the prices of RAM are having come down, the databases could be used to store information on the about art works, medical images like CT scan, satellite images, nature photography, album images, images of convicts i.e., criminals for security purpose, giving rise to a massive data having a diverse image set collection. This leads us to the problem of relevant image retrieval from a huge database having diverse image set collection. Web search engines are always expected to deliver flawless results in a short span of time including accuracy and speed. An image search engine also comes under the same roof. The results of an image search should match with the best available image from in the database. Content Based Image Retrieval (CBIR) has been proposed to enable these image search engines with impeccable results. In this CBIR technology, using only color and texture as parameters for zeroing in on an imagemay not help in fetching the best result. Also most of the existing systems uses keyword based search which could yield inappropriate results. All the above mentioned drawbacks in CBIR have been addressed in this research. A complete analysis of CBIR including a combination of features has been carried out, implemented and tested.