Browser & Editor for efficient image search using re-ranking method

  Miss. Kashmira Mandore

Image re-ranking, as an effective way to improve the results of web-based image search, has been adopted by current commercial search engines. Ambiguity of query images is hard to describe accurately by using keywords. Given a query keyword, pools of images are first retrieved by the search engine based on textual information. By asking the user to select a query image from the pool, the remaining images are re-ranked based on their visual similarities with the query image. A major challenge is that the similarities of visual features do not well correlate with images’ semantic meanings which interpret users’ search intention. On the other hand, learning a universal visual semantic space to characterize highly diverse images from the web is difficult and inefficient. So, here is a novel image re-ranking framework, which automatically offline learns different visual semantic spaces for different query keywords through keyword expansions. The visual features of images are projected into their related visual semantic spaces to get semantic signatures. At the online stage, images are re-ranked by comparing their semantic signatures obtained from the visual semantic space specified by the query keyword. The new approach significantly improves both the accuracy and efficiency of image re-ranking

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Unique Identification Number - IJEDR1601056
Page Number(s) - 355-358
Pubished in - Volume 4 | Issue 1 | February 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Miss. Kashmira Mandore,   "Browser & Editor for efficient image search using re-ranking method", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 1, pp.355-358, February 2016, Available at :http://www.ijedr.org/papers/IJEDR1601056.pdf