Abstract: The current image retrieval systems are successful in retrieving images, using keyword based approaches. However, they are incapable to retrieve the images which are context sensitive and annotated inappropriately. Content-Based Image Retrieval (CBIR) aims at developing techniques that support effective searching and browsing of large image repositories, based on automatically derived image features. The current CBIR systems suffer from the semantic gap. Though a user feedback is suggested as a remedy to this problem, it often leads to distraction in the search. To overcome these disadvantages, novel interactive keyword based image retrieval and integrating text with image content are proposed to enhance the retrieval accuracy. Also GOOGLE search engine is used as a back end to search and retrieved images with their link. The robustness of the result obtained by the proposed method is shown by various performance analyses like different web browsers, different internet service providers and etc.
Keywords:- Context sensitive, Annotation, Content-Based Image Retrieval, Google search engine
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