Abstract
This article provides and compares two color-based image retrieval techniques for RGB image databases. Our proposed CBIR systems use the query by example approach and a relevance feedback mechanism. The feature extraction process is performed by computing a global color histogram for each image. Feature vectors are first compared using the histogram intersection difference metric. A distance based on Chi-squared measure is also proposed. A relevance feedback mechanism is used in the retrieval process in both retrieval cases.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lew, M., et al.: Content-based Multimedia Information Retrieval: State of the Art and Challenges. Phil. Trans. Roy. Soc. London A247, 529–551 (1955)
Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image Retrieval: Ideas, Influences, and Trends of the New Age. ACM Computing Surveys 40(2), 1–60 (2008)
Inoue, M.: On the need for annotation-based image retrieval. In: Workshop on Information Retrieval in Context, pp. 44–46 (2004)
Eakins, J., Grahalm, M.: Content-based Image Retrieval. JISC Technology Applications Programme Report 39 (1999)
Smith, J., Chang, S.-F.: Tools and techniques for color image retrieval. In: Symposium on Electronic Imaging: Science and Technology - Storage & Retrieval for Image and Video Databases IV, IS&T/SPIE, San Jose, CA, vol. 2670 (February 1996)
Smith, J., Chang, S.-F.: Texture classification and discrimination in large image databases. In: Proceedings of the IEEE International Conference on Image Processing (ICIP 1994) (November 1994)
Dimov, D.: Fast, Shape Based Image Retrieval. In: Proceedings of International Conference on Computer Systems and Technologies, CompSysTech 2003 (2003)
Alsberg, I.: Incremental relevance feedback. In: Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Copenhagen, pp. 11–22 (1992)
Pass, G., Zabih, R.: Histogram refinement for content-based image retrieval. In: Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV 1996), p. 96 (1996)
Barbu, T.: Modeling Multimedia Information Systems. Romanian Academy Publishing House (2006) (in Romanian)
Barbu, T., Ciobanu, A.: Color-based image retrieval technique using relevance feedback. In: Proceedings of ECAI 2009, Pitesti, Romania, July 2009, vol. 4, pp. 105–108 (2009)
Swain, M., Ballard, D.: Color indexing. International Journal of Computer Vision 7(1), 11–32 (1991)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Barbu, T., Costin, M., Ciobanu, A. (2013). Color-Based Image Retrieval Approaches Using a Relevance Feedback Scheme. In: Balas, V., Fodor, J., Várkonyi-Kóczy, A. (eds) New Concepts and Applications in Soft Computing. Studies in Computational Intelligence, vol 417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28959-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-28959-0_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28958-3
Online ISBN: 978-3-642-28959-0
eBook Packages: EngineeringEngineering (R0)