Main Article Content

Shweta Gonde
Prof. Uday Chourasia, Prof. Raju Barskar


Images are the increases day by day on the Internet. Retrieving relevant images from a large collection of database has become an important research topic. This paper focus on the reranking of images by utilizing the both the visual and textual features, so given a textual query in traditional image retrieval, relevant images are to be re-ranked using visual features after the initial text-based search. Here first query keywords are utilize for separating the dataset images into two group of relevant image and irrelevant image then all the images are ranked base on the image different modality of image features as the similar images need to be display closer. Using single modality is not effective as different image need different kind of feature for analysis and it was obtained in experimental that the proposed re-ranking approach has better performances than using single modality.


Keywords— Information Extraction, Text Analysis, Ontology, feature extraction, text categorization, clustering


Download data is not yet available.

Article Details