An effective similarity measure via genetic algorithm for Content-Based Image Retrieval with extensive features Online publication date: Fri, 04-May-2012
by Baddeti Syam; Yerravarapu Srinivasa Rao
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 5, No. 1, 2012
Abstract: With the aid of image content, the relevant images can be extracted from the image in the Content Based Image Retrieval (CBIR) system. Concise feature sets limit the retrieval efficiency, to eliminate this shape, colour, texture and contourlet features are extracted. For retrieving relevant images, the optimisation technique Genetic Algorithm (GA) is utilised and for similarity measure Squared Euclidean Distance (SED) is utilised for comparing query image featureset and database image featureset. Hence, from GA based similarity measure, relevant images are retrieved and evaluated by querying different images.
Online publication date: Fri, 04-May-2012
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