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A Discontinuity Adaptive Method for Super-Resolution of License Plates

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Computer Vision, Graphics and Image Processing

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4338))

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Abstract

In this paper, a super-resolution algorithm tailored to enhance license plate numbers of moving vehicles in real traffic videos is proposed. The algorithm uses the information available from multiple, sub-pixel shifted, and noisy low-resolution observations to reconstruct a high-resolution image of the number plate. The image to be super-resolved is modeled as a Markov random field and is estimated from the low-resolution observations by a graduated non-convexity optimization procedure. To preserve edges in the reconstructed number plate for better readability, a discontinuity adaptive regularizer is proposed. Experimental results are given on several real traffic sequences to demonstrate the edge preserving capability of the proposed method and its robustness to potential errors in motion and blur estimates. The method is computationally efficient as all operations are implemented locally in the image domain.

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Author information

Authors and Affiliations

  1. Image Processing and Computer Vision Laboratory, Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, 600 036, India

    K. V. Suresh & A. N. Rajagopalan

Authors
  1. K. V. Suresh
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  2. A. N. Rajagopalan
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, IIT Delhi, New Delhi, India

    Prem K. Kalra

  2. School of Computer Science and Engineering, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel

    Shmuel Peleg

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© 2006 Springer-Verlag Berlin Heidelberg

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Suresh, K.V., Rajagopalan, A.N. (2006). A Discontinuity Adaptive Method for Super-Resolution of License Plates. In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_3

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  • DOI: https://doi.org/10.1007/11949619_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68301-8

  • Online ISBN: 978-3-540-68302-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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