期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：3
出版社：S.S. Mishra
摘要：Image search has become a popular feature in many search engines, including Google, Yahoo!, MSN, etc., majority of which use very little, if any, image information[1]. Image Retrieval system is a powerful tool in order to manage large scale image databases. Retrieving images from large and varied co llections using image content as a key is a challenging and important problem. Due to the success of text based search of Web pages and in part, to the difficulty and expense of using image based signals, most search engines return images solely based on the text of the pages from which the images are linked. No image analysis takes place to determine relevance/quality. This can yield results of inconsistent quality. So, such kind of visual search approach has proven unsatisfying as it often entirely ignores the visual content itself as a ranking signal. To address this issue, we present a new image ranking and retrieval technique known as visual reranking, defined as reordering of visual images based on their visual appearance. This approach relies on analyzing the distribution of visual similarities among the images and image ranking system that finds the multiple visual themes and their relative strengths in a large set of images. The major advantages of this approach is that, it improves the search performance by reducing the number of irrelevant images acquired as the result of image search and provides quality consistent output. Also, it perfo rms text based search on database to get ranked images and extract features of them to obtain reranked images by visual search
关键词：Text Based Image Retrieval; Image Ranking & Retrieval Techniques; Pyramid Structure Wavelet ;Transform; Content Based Image Retrieval; Visual Reranking.
