Optimize visual image search for semantic web

Abstract: In today’s web image search engines find more irrelevances in the search result. By adding semantic meaning to the document this irrelevance can be reduced. SIEVE image search algorithm combine the text based and content based method and shows the result. Also “IN-Picture” search algorithm mixing the images higher level and lower level contents. In this paper it shows some image searching framework like “SAFE” describe how image are searched using its attributes. Also describes some semantic web technology, which helps in image search and shows how detailed indexing system can use SPARQL query and ontology of an image to build semantic web based framework.

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