Relevance and Diversity of Images by Using Tags

Now a day, there is a growth of digital images and video archives. Some of these are very important from user point of view. The collection of these digital images may be for personal use and may be for public use. For searching images in the database, there is the need of secure, fast and efficient techniques. Tag-based image search is an effective technique to find images in the databases and in the social websites. In this paper a reranking system for image retrieval with the consideration of images relevance and diversity is proposed. Reranking of the images have done according to their visual features and semantic features. Visual features are used for detecting duplicate images in proposed method. Each user maintains several images. First sort these images by same group user ranking system. Users that have higher contribution to the given query rank higher. Then an implementation to all-user reranking on the ranked users image set and only the most relevant image from users image set is selected. These selected images compose the final retrieval results. We build an inverted structure for the image dataset to speed up the searching process.