Abstract
The aim of this paper is to discuss a fusion of the two most popular image features - color and shape - in the aspect of content-based image retrieval. It is clear that these representations have their own advantages and drawbacks. Our suggestion is to combine them to achieve better results in various areas, e.g. pattern recognition, object representation, image retrieval, by using optimal variants of particular descriptors (both, color and shape) and utilize them in the same time. To achieve such goal we propose two general strategies (sequential and parallel) for joining elementary queries. They are used to construct a system, where each image is being decomposed into regions, basing on shapes with some characteristic properties - color and its distribution. In the paper we provide an analysis of this proposition as well as the initial results of application in Content Based Image Retrieval problem. The original contribution of the presented work is related to the fusion of several shape and color descriptors and joining them into parallel or sequential structures giving considerable improvements in content-based image retrieval. The novelty is based on the fact that many existing methods (even complex ones) work in the same domain (shape or color), while the proposed approach joins features from different areas.
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References
Bober M.: MPEG-7 Visual Shape Descriptors, IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 6 (2001) 716–719
Deng Y., Manjunath B. S., Kenney C., Moore M. S., Shin H.: An Efficient Color Representation for Image Retrieval, IEEE Transactions on Image Processing, vol. 10, no. 1 (2001) 140–147
Foggia P., Sansone C., Tortorella F., Vento M.: Combining statistical and structural approaches for handwritten character description, Image and Vision Computing, vol. 17, no. 9 (1999) 701–711
Jain A. K.: Fundamentals of Digital Image Processing, Prentice Hall, 1989
Kukharev G., Miklasz M.: Face Retrieval from Large Database, Polish Journal of Environmental Studies, vol. 15, no. 4C (2006) 111–114
Kuncheva L.I.: Combining classifiers: Soft computing solutions, in: Pattern Recognition: From Classical to Modern Approaches, World Scientific Publishing Co., Singapore (2001) 427–452
Kuncheva L.I.: A theoretical study on six classifier fusion strategies, IEEE Transactions on PAMI, 24, no. 2 (2002) 281–286
Loncaric S.: A survey on shape analysis techniques, Pattern Recognition, vol. 31, iss. 8 (1998) 983–1001
Manjunath B. S., Ohm J.-R., Vasudevan V. V., Yamada A.: Color and Texture Descriptors, IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 6 (2001) 703–715
Mehtre B. M., Kankanhalli M. S., Lee W. F.: Shape measures for content based image retrieval: a comparison, Information Proc. & Management, vol. 33 (1997) 319–337
Rauber T.W., Steiger-Garcao A.S.: 2-D form descriptors based on a normalized parametric polar transform (UNL transform), Proc. MVA’92 IAPR Workshop on Machine Vision Applications (1992)
Wood J.: Invariant pattern recognition: a review, Pattern Recognition, vol. 29, iss. 1 (1996) 1–17
Zhang D., Lu G.: Review of shape representation and description techniques, Pattern Recognition, vol. 37, iss. 1 (2004) 1–19
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Forczmański, P., Frejlichowski, D. (2007). Strategies of Shape and Color Fusions for Content Based Image Retrieval. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_1
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DOI: https://doi.org/10.1007/978-3-540-75175-5_1
Publisher Name: Springer, Berlin, Heidelberg
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