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Object-Based Image Search Using Color and Texture Homogeneous Regions

유사한 색상과 질감영역을 이용한 객체기반 영상검색

  • 유헌우 (고려대학교 산업시스템정보공학과) ;
  • 장동식 (고려대학교 산업시스템정보공학과) ;
  • 서광규 (KIST CAD/CAM연구센터)
  • Published : 2002.06.01

Abstract

Object-based image retrieval method is addressed. A new image segmentation algorithm and image comparing method between segmented objects are proposed. For image segmentation, color and texture features are extracted from each pixel in the image. These features we used as inputs into VQ (Vector Quantization) clustering method, which yields homogeneous objects in terns of color and texture. In this procedure, colors are quantized into a few dominant colors for simple representation and efficient retrieval. In retrieval case, two comparing schemes are proposed. Comparing between one query object and multi objects of a database image and comparing between multi query objects and multi objects of a database image are proposed. For fast retrieval, dominant object colors are key-indexed into database.

References

  1. M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker, 'Query byimage content: The QBIC system,' IEEE Computer, vol. 28, no. 9, pp. 23-31, September, 1995 https://doi.org/10.1109/2.410146
  2. A. Pentland, R. W. Picard, and S. Sclaroff, 'Photobook: Content-based manipulation of imagedatabases,' International Journal of Computer Vision, vol 18, no. 3, pp. 233-254, 1996 https://doi.org/10.1007/BF00123143
  3. J. R. Bach, C. Fuller, A. Gupta, A. Hampapur, B. Horowitz, R. Humphrey, R. C. Jain and C. Shu, 'The virage image search engine: An openframework for image management,' In Proc. SPIE Vol. 2670: Storage and Retrieval for Images and Video Databases Ⅳ, pp. 76-86, February, 1996 https://doi.org/10.1117/12.234785
  4. J. R. Smith and S. E. Chang, 'A fully automated content-based image query system,' in Proc. ACM Multimedia, pp.87-98, November, 1996
  5. W. Y. Ma and B. S. Majunath, 'Natra: A toolboxfor navigating large image databases,' Multimedia Sytems, vol. 7, no. 3, pp. 184-198, 1999 https://doi.org/10.1007/s005300050121
  6. S. Belongie, C. Carson, H. Greenspan, and J. Malick, 'Color and texture-based image segmentation using EM and its application to content-based image retrieval,' Proc. International Conterence on Computer Vision, pp. 675-682, January, 1988
  7. C. Faloutsos, M. Flickner, W. NIblack, D. Petkovic, W. Equitz, and R. Barber, 'Efficient and effective querying by image content,' Technical Report, IBM Research Report, 1993
  8. T. S. Chua, K. L. Tan, and B. C. Ooi, 'Fastsigniture-based color-spatial image retrieval,' in Proc. IEEE Conf. on Multimedia Computing and Systems, pp. 362-369, 1997 https://doi.org/10.1109/MMCS.1997.609637
  9. H. Lu, B. Ooi, and K. Tan, 'Efficient image retrieval by color contents,' in Proc. of the 1994 International Conference on Applications of Databases, pp. 95-108, 1994 https://doi.org/10.1007/3-540-58183-9_43
  10. J. Huang, S. Kumar, M. Mitra, W. J. Zhu, and R. Sabih, 'Image indexing using color correlogram,' in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 762-768, 1997 https://doi.org/10.1109/CVPR.1997.609412
  11. Y. Chahir and L. Chen, 'Searching images on the Basis of color homogeneous objects and their spatial relationship,' Journal of Visual Communication and Image Representation, vol. 11, no. 3, pp. 302-326, 2000 https://doi.org/10.1006/jvci.1999.0428
  12. A. S. Pandya and R. B. Macy, 'Pattern recognition with neural networks in C++,' IEEE Press, 1995
  13. B. M. Mehtre, M. S. Kankanhalli, A. D. Narasimhalu, and G. C. Man, 'Color matching for image retrieval,' Pattern Recognition Letters, vol. 16, no.3, pp. 325-331, 1995 https://doi.org/10.1016/0167-8655(94)00096-L