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Content Based Image Retrieval Methods Using Self Supporting Retrieval Map Algorithm


P.Jayaprabha, Rm.Somasundaram


Vol. 13  No. 1  pp. 141-147


The need to have a versatile and general purpose content based image retrieval (CBIR) system for a very large image database has attracted focus of many researchers of information technology-giants and leading academic institutions for development of CBIR techniques. In a high-level semantic retrieval process, we utilize the search engine to retrieve a large number of imagesusing a given text-based query. In a low level image retrieval process, the system provides a similar image search function for the user to update the input query for image similarity characterization. The revolutionary internet and digital technologies have imposed a need to have a system to organize abundantly available digital images for easy categorization andretrieval. These techniques encompass diversified areas, viz. image segmentation, image feature extraction, representation, mapping of features to semantics, storage and indexing, image similarity distance measurement and retrieval making CBIR system development a challenging task. The state of the art techniques are reviewedand future scope is cited. The experimental evaluations based on coverage ratio measure show that our scheme significantly improves the retrieval performance of existing image search engine.


CBIR, Image feature extraction, Imageanalysis, Image retrieval, Image search, Image similarity