IMAGE PREPROCESSING FOR CBIR SYSTEM

Tatiana Jaworska

Abstract

This article describes the way in which image is prepared for content-based image retrieval system. Our CBIR system is dedicated to support estate agents. In our database there are images of houses and bungalows. All efforts have been put into extracting elements from an image and finding their characteristic features in the unsupervised way. Hence, the paper presents segmentation algorithm based on a pixel colour in RGB colour space. Next, it presents the method of object extraction in order to obtain separate objects prepared for the process of introducing them into database and further recognition. Moreover, a novel method of texture identification which is based on wavelet transformation, is applied.

References

  1. Bezdek, J. C., 1981. Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York.
  2. Fauzi, M., Lewis, P., 2006. Automatic texture segmentation for content-based image retrieval application, Pattern Analysis and Applications, Springer-Verlag, London, (in printing).
  3. Flickner, M., Sawhney, H., et al., 1995. Query by Image and Video Content: The QBIC System, IEEE Computer, Vol. 28, No. 9, pp. 23-32.
  4. Haralick, R. M., Shanmugan, K., Dinstein, I., 1973. Texture Features for Image Classification, IEEE Transactions of Systems, Man and Cyberntics, SMC-3, pp. 610-621.
  5. Hsu, W., Chua, T. S., Pung, H. K., 2000. Approximation Content-based Object-Level Image Retrieval, Multimedia Tools and Applications, Vol. 12, Springer Netherlands, pp. 59-79.
  6. Jaworska, T., Partyka, A., 2005. Research: Content-based image retrieval system [in Polish], Report RB/37/2005, Systems Research Institute, PAS.
  7. Mokhtarian, F., Abbasi, S., Kittler J., 1996. Robust and Efficient Shape Indexing through Curvature Scale Space, Proc. British Machine Vision Conference, pp. 53-62.
  8. Niblack, W., Flickner, M., et al., 1993. The QBIC Project: Querying Images by Content Using Colour, Texture and Shape, SPIE, Vol. 1908, pp. 173-187.
  9. Ogle, V., Stonebraker, M., 1995. CHABOT: Retrieval from a Relational Database of Images, IEEE Computer, Vol. 28, No 9, pp. 40-48.
  10. Russ, J. C., 1995 The image processing. Handbook, CRC, London, pp. 361-385.
  11. Seber, G., 1984. Multivariate Observations, Wiley.
  12. Spath, H., 1985. Cluster Dissection and Analysis: Theory, FORTRAN Programs, Examples, translated by J. Goldschmidt, Halsted Press, pp. 226.
  13. Tan, K-L., Ooi, B. Ch., Yee, Ch. Y., 2001. An Evaluation of Color-Spatial Retrieval Techniques for Large Image Databases, Multimedia Tools and Applications, Vol. 14, Springer Netherlands, pp. 55-78.
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Paper Citation


in Harvard Style

Jaworska T. (2007). IMAGE PREPROCESSING FOR CBIR SYSTEM . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-972-8865-84-9, pages 375-378. DOI: 10.5220/0001644303750378


in Bibtex Style

@conference{icinco07,
author={Tatiana Jaworska},
title={IMAGE PREPROCESSING FOR CBIR SYSTEM},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2007},
pages={375-378},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001644303750378},
isbn={978-972-8865-84-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - IMAGE PREPROCESSING FOR CBIR SYSTEM
SN - 978-972-8865-84-9
AU - Jaworska T.
PY - 2007
SP - 375
EP - 378
DO - 10.5220/0001644303750378