CONTENT BASED IMAGE RETRIEVAL USING HYBRID-SVM

Rajneesh Pachauri, Meenakshi Pandey

Abstract


The goal of content based image retrieval is to retrieve the images that users want to search. Content based Image retrieval systems attempt to search through a database to find images that are perceptually similar to a query image. Set of low-Level visual features (Color, Shape and Texture) are used to represent an image in most modern content based image retrieval systems. Therefore, between high-level information and low-level features a gap exists, which are the main reason that down the improvement of the image retrieval accuracy.In this paper Hybrid support vector machine (SVM) method proposed to retrieve several features and shorten the semantic gap between low-level visual feature and high-level perception. Image data set is taken from coral image data set. MATLAB 2009a is used as a simulator to analysis the proposed work.

Keywords


CBIR, hybrid SVM, Semantic gap

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DOI: https://doi.org/10.26483/ijarcs.v9i2.5809

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