Abstract
A retrieval methodology which integrates color, texture and shape information is presented in this paper. Consequently, the overall image similarity is developed through the similarity based on all the feature components. Alternatively to known CBIR systems, we compute features only in the finite number of extracted ROIs. There are some other known methods of determining ROIs, but our method of extracting ROI based on points of interest detection and Gabor filtration, enables to use filter responses also to describe texture parameters. The described method was tested on a small post stamps database (130 stamps), for which we achieved comparable results as for Blobworld system. Presented method is further developed in postal image analysis and retrieval system.
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References
Teh C C, Chin R T (1988) On image analysis by the methods of moments, IEEE Trans. Pattern Anal. Machine Intell., vol. 10, pp. 496–513
Haralick R, Shanmugam K, Dinstein I (1973) Textural features for image classification, IEEE Trans. on Systems, Man, and Cybernetics, SMC-3(6), pp.610–621
Khotanzad A, Hong Y H (1990) Invariant image recognition by Zernike moments, IEEE Trans. Pattern Anal. Machine Intell., 12(5), 489–498
Andrysiak T, Choraś M (2003) Hierarchical Object Recognition Using Gabor Wavelets, Proc of KOSYR, 271–278
Choraś R (2003) Content-Based Retrieval Using Color, Texture, and Shape Information. In Sanfeliu A, Ruiz-Shulcloper J (eds): Progress in Pattern Recognition, Speech and Image Analysis, Springer, Berlin Heidelberg New York
Fogel I, Sagi D (1989) Gabor filters as texture discriminator, Biological Cybernetics, 61: 103–113
Jain A, Farrokhnia F (1991) Unsupervised texture segmentation using Gabor filters, Pattern Recognition, 24(12):1167–1186
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© 2005 Springer-Verlag Berlin Heidelberg
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Choraś, R.S., Andrysiak, T., Choraś, M. (2005). Content Based Image Retrieval Technique. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_43
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DOI: https://doi.org/10.1007/3-540-32390-2_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
Online ISBN: 978-3-540-32390-7
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