Abstract
Visual information is becoming more important and at a rapid rate. However, creators and users are reluctant to annotate visual content making it difficult to search these collections. Content-based image retrieval (CBIR) techniques extract visual descriptors directly from image data and can hence be used in situations where textual information is not available. In this paper, we give a brief introduction on some of the basic colour descriptors that are employed in CBIR.
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References
Osman, T., Thakker, D., Schaefer, G., Lakin, P.: An integrative semantic framework for image annotation and retrieval. In: IEEE/WIC/ACM International Conference on Web Intelligence, pp. 366–373 (2007)
Rodden, K.: Evaluating Similarity-Based Visualisations as Interfaces for Image Browsing. PhD thesis, University of Cambridge Computer Laboratory (2001)
Smeulders, A., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Analysis and Machine Intelligence 22, 1249–1380 (2000)
Stricker, M., Orengo, M.: Similarity of color images. In: Conf. on Storage and Retrieval for Image and Video Databases III. Proceedings of SPIE, vol. 2420, pp. 381–392 (1995)
Swain, M., Ballard, D.: Color indexing. Int. Journal of Computer Vision 7, 11–32 (1991)
Rubner, Y., Tomasi, C., Guibas, L.: The earth mover’s distance as a metric for image retrieval. Int. Journal of Computer Vision 40, 99–121 (2000)
Pass, G., Zabih, R.: Histogram refinement for content-based image retrieval. In: 3rd IEEE Workshop on Applications of Computer Vision, pp. 96–102 (1996)
Schaefer, G.: Content-based retrieval of compressed images. In: International Workshop on DAtabases, TExts, Specifications and Objects, pp. 175–185 (2010)
Plant, W., Schaefer, G.: Visualisation and browsing of image databases. In: Lin, W., Tao, D., Kacprzyk, J., Li, Z., Izquierdo, E., Wang, H. (eds.) Multimedia Analysis, Processing and Communications. SCI, vol. 346, pp. 3–57. Springer, Heidelberg (2011)
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Schaefer, G. (2011). Mining Image Databases by Content. In: Fernandes, A.A.A., Gray, A.J.G., Belhajjame, K. (eds) Advances in Databases. BNCOD 2011. Lecture Notes in Computer Science, vol 7051. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24577-0_7
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DOI: https://doi.org/10.1007/978-3-642-24577-0_7
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