• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Content Based Image Retrieval Using Combined Features of Shape, Color and Relevance Feedback


Abstract

Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.


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Cite this article

[IEEE Style]
Yasmin Mussarat, Sharif Muhammad, Mohsin Sajjad and Irum Isma, "Content Based Image Retrieval Using Combined Features of Shape, Color and Relevance Feedback," KSII Transactions on Internet and Information Systems, vol. 7, no. 12, pp. 3149-3165, 2013. DOI: 10.3837/tiis.2013.12.011

[ACM Style]
Mussarat, Y., Muhammad, S., Sajjad, M., and Isma, I. 2013. Content Based Image Retrieval Using Combined Features of Shape, Color and Relevance Feedback. KSII Transactions on Internet and Information Systems, 7, 12, (2013), 3149-3165. DOI: 10.3837/tiis.2013.12.011