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An Image Retrieval Method Based on Color-Complexity and Spatial-Histogram Features

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Języki publikacji
EN
Abstrakty
EN
This paper proposes two kinds of image features. One feature is the spatial-histogram feature. It combines the color histogram feature and the information about the dimensional position of pixels in an image to record the distribution of the pixels' colors that are present in different spatial positions within an image. The other image feature proposed in this paper is the color-complexity feature, which can be used to describe the change of pixel colors in the image. From the experimental results, ANMRR value is provided and we observe that the image retrieval system based on these two kinds of image features can provide a fairly good accuracy rate in image retrieval. Moreover, it has the capacity to tolerate errors; that is, for images that are damaged by rotation, shift, or color variant attacks, their similar image pairs can still be retrieved from the image database. Thus, the accuracy and flexibility of the image retrieval system are drastically improved.
Wydawca
Rocznik
Strony
481--493
Opis fizyczny
bibliogr. 13 poz., tab., rys.
Twórcy
autor
autor
  • Department of Information Management, National Taichung Institute of Technology, 129 Sec. 3, San-min Rd., Taichung, Taiwan 404, R.O.C., wuhc@ntit.edu.tw
Bibliografia
  • [1] M. Adoram and M. S. Lew, "IRUS: Image Retrieval Using Shape," Proceedings of IEEE International Conference on Multimedia Computing and System, Vol. 2, pp. 597-602, 1999.
  • [2] R. Brunelli and O. Mich, "Histograms Analysis for Image Retrieval," Pattern Recognition, Vol. 34, No. 8, pp. 1625-1637, 2001.
  • [3] Y. K. Chan, and C. C. Chang, "A Color Image Retrieval System Based on the Run-Length Representation," Pattern Recognition Letter, Vol. 18, pp. 447-455, 2001.
  • [4] Y. K. Chan, and C. C. Chang, "A Color Image Retrieval Method Based on Color Moment and Color Variance of Adjacent Pixels," International Journal of Pattern Recognition and Artificial Intelligent, Vol.16, No.1, pp. 113-125, 2002.
  • [5] Y. Deng, B. S. Manjunath, C. Kenney, M. S. Moore and H. Shin, "An Efficient Color Representation for Image Retrieval," IEEE Transactions on Image Processing, Vol. 10, No. 1, pp. 140-147, Jan. 2001.
  • [6] C. S. Fuh, S.W. Cho and K. Essig, "Hierarchical Color Image Region Segmentation for Content-Based Image Retrieval System," IEEE Transactions on Image Processing, Vol. 9, No. 1, pp. 156-162, Jan. 2000.
  • [7] K. Fukunaga, Introduction to Statistical Pattern Recognition, San Diego, CA, Academic Press, 1990.
  • [8] M. S. Kankanhalli, B. M. Mehtre and H. Y. Huang, "Color and Spatial Feature for Content-based Image Retrieval," Pattern Recognition, Vol. 22, Issue:3-4, pp. 323-337, Mar. 2001.
  • [9] M.S. Lew and D. Denteneer, "Fisher Keys for Content Based Retrieval," Image and Vision Computing, Vol.19, Issue: 8, pp. 561-566, May 2001.
  • [10] B. M. Mehtre, M. S. Kankanhali, A. D. Narasimhalu and G. C. Man, "Color Matching for Image Retrieval," Pattern Recognition Letter, Vol. 16, pp. 325-331, 1995.
  • [11] P. Pala and S. Santini, "Image Retrieval by Shape and Texture," Pattern Recognition, Vol. 32, Issue: 3, pp. 517-527, Mar. 1999.
  • [12] K. Shearer, S. Venkatesh and D. Kieronska, "Spatial Indexing for Video Databases," Journal of Visual Communication and Image Representation, Vol. 7, No. 4, pp. 325-335, 1996.
  • [13] ISO/IEC JTC1/SC29/WG11- MPEG/M5984, "Core experiments on MPEG-7 edge histogram descriptors," Geneva, Switzerland, May 2000.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS5-0009-0056
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