Analysis Of Reranking Techniques For Web Image Search With Attribute –Assisted
Journal Title: International Journal of Science Engineering and Advance Technology - Year 2016, Vol 4, Issue 9
Abstract
Many commercial search engines such as Google, Yahoo and Bing have been adopted this strategy. The search engines are mostly based on text and constrained due to user search by keyword which results into ambiguity among images. The noisy or irrelevant images may be present in the retrieved results. The purpose of web image search re-ranking is to reorder retrieved elements to get optimal rank list. The existing visual reranking schemes improve text-based search results by making the use of visual information. These methods are based on low-level visual features, and do not take into account the semantic relationship among images. Semantic attribute assisted re-ranking is proposed for web image search. Using the classifiers for predefined attributes, each image is represented by attribute features. The hypergraph is used to model the relationship between images. Hypergraph ranking is carried out to order the images. The basic principle is that similar images should have similar ranking. This paper presents a detail review of different image retrieval and reranking approaches. The purpose of the survey is to provide an overview and analysis of the functionality, merits, and demerits of the existing image reranking systems, which can be useful for researchers for developing effective system with more accuracy.
Authors and Affiliations
Kiranmai Madireddi| M.Tech (CSE) Student, Nimra College of Engineering & Technology, A.P., India, P. Lakshmana Rao| Assistant Professor, Dept. of Computer Science & Engineering, Nimra College of Engineering & Technology, A.P., India, Sayeed Yasin| Associate professor & Head, Dept. of Computer Science & Engineering, Nimra College of Engineering & Technology, A.P., India
Keywords
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