Colour and Texture Feature Based Hybrid Approach for Image Retrieval

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 166)

Abstract

The Content Based Image Retrieval (CBIR) is a technique that works on images and in response extracts relevant images. A novel hybrid two stage universal CBIR technique using both colour and texture features extraction is proposed in this paper. In the first stage for colour feature extraction, colour moments up to the fourth order are extracted and are used in deriving the respective histograms which forms the colour feature vector. In the second stage for the texture feature extraction the CCM (Colour Co-occurrence Matrix) technique employed takes into account the correlation between the RGB colour bands in all the eight directions while computing the texture features. In every stage the distance between the query image and the image in the database is calculated by using relative distance measure. The resultant distance between the query image and the image in the database is calculated by using a weighted distance classifier. Thus, a hybrid fusion method is achieved that has better performance than other colour-spatial based methods and promises to give more relevant output to the user.

Keywords

CBIR local statistics histograms Skew Kurtosis CCM 

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Ramrao Adik Institute of TechnologyNavi - MumbaiIndia

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