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Computer Vision and Graphics pp 197–202Cite as

VEHICLE DETECTION USING GABOR FILTERS AND AFFINEMOMENTINVARIANTS FROM IMAGE DATA

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Part of the book series: Computational Imaging and Vision ((CIVI,volume 32))

Abstract

This paper proposes a new method for detecting vehicles from an image. The method consists in three stages of segmentation, extraction of candidate window corresponding to a vehicle and detection of a vehicle. From the experimental results using 121 real images of road scenes, it is found that the proposed method can successfully detect vehicles for 120 images among 121 images.

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REFERENCES

  1. Z. Duric, et al., Estimating relative vehicle motions in traffic scenes, Pattern Recognition, Vol.35 (2002) pp. 1339–1353.

    Article  MATH  Google Scholar 

  2. D. W. Murray and B. F. Buxton, Scene segmentation from visual motion using global optimization, IEEE Trans. on PAMI, Vol.9, No.2 (1987) pp. 220–228.

    Google Scholar 

  3. X. Li, Z. Q. Liu and K. M. Leung, Detection of vehicles from traffic scenes using fuzzy integrals, Pattern Recognition, Vol.35 (2002) pp. 967–980.

    Google Scholar 

  4. A. K. Jain, N. K. Ratha and S. Lakshmanan, Object detection using Gabor filters, Pattern Recognition, Vol.30 (1997) pp.295–309.

    Google Scholar 

  5. G. Adiv, Determining three-dimensional motion and structure from optical flow generated by several moving objects, IEEE Trans. on PAMI, Vol.7, No.4 (1985) pp. 384–401.

    Google Scholar 

  6. K. Kawada and S. Arimoto, Hierarchical texture analysis using Gabor expansion, J. of the Institute of Electronics, Information and Communication Engineers, Vol. J78-DII, No.3 (1995) pp.437–444.

    Google Scholar 

  7. J. Flusser and T. Suk, Pattern recognition by affine moment invariants, Pattern Recognition, Vol.26 (1993) pp. 167–174.

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Kyoto Institute of Technology, Kyoto 606-8585, Matsugasaki, Sakyo-ku, Japan

    Tadayoshi Shioyama, Mohammad Shorif Uddin & Yoshihiro Kawai

Authors
  1. Tadayoshi Shioyama
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  2. Mohammad Shorif Uddin
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  3. Yoshihiro Kawai
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Editor information

Editors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    K. Wojciechowski

  2. Silesian University of Technology, Gliwice, Poland

    B. Smolka

  3. Silesian University of Technology, Gliwice, Poland

    H. Palus

  4. The University of Western Australia, Crawley, Australia

    R.S. Kozera

  5. Warsaw University of Technology, Warsaw, Poland

    W. Skarbek

  6. The University of Western Australia, Crawley, Australia

    L. Noakes

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© 2006 Springer

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Shioyama, T., Uddin, M.S., Kawai, Y. (2006). VEHICLE DETECTION USING GABOR FILTERS AND AFFINEMOMENTINVARIANTS FROM IMAGE DATA. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_28

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  • DOI: https://doi.org/10.1007/1-4020-4179-9_28

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-4178-5

  • Online ISBN: 978-1-4020-4179-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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