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Blind Image Deconvolution of Linear Motion Blur

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Computer Vision, Imaging and Computer Graphics. Theory and Applications (VISIGRAPP 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 274))

Abstract

We present an efficient method to deblur images for information recognition. The method is successfully applied directly on mobile devices as a preprocessing phase to images of barcodes. Our main contribution is the fast identifaction of blur length and blur angle in the frequency domain by an adapted radon transform. As a result, the barcode recognition rate of the deblurred images has been increased significantly.

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Author information

Authors and Affiliations

  1. RheinMain University of Applied Sciences, Wiesbaden, Germany

    Florian Brusius, Ulrich Schwanecke & Peter Barth

Authors
  1. Florian Brusius
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  2. Ulrich Schwanecke
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  3. Peter Barth
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Editor information

Editors and Affiliations

  1. Xerox Research Centre Europe, 6 ch. de Maupertuis, 38240, Meylan, France

    Gabriela Csurka

  2. Aalborg University, Niels Jernes Vej 14, 3-215A, 9220, Aalborg Ø, Denmark

    Martin Kraus

  3. Department of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia

    Leonid Mestetskiy

  4. LISA-ISTIA, Université d’Angers, 62, avenue Notre-Dame du Lac, 49000, Angers, France

    Paul Richard

  5. Departamento de Sistemas e Informática, Escola Superior de Tecnologia do IPS, Rua do Vale de Chaves Estefanilha, 2910, Setúbal, Portugal

    José Braz

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Brusius, F., Schwanecke, U., Barth, P. (2013). Blind Image Deconvolution of Linear Motion Blur. In: Csurka, G., Kraus, M., Mestetskiy, L., Richard, P., Braz, J. (eds) Computer Vision, Imaging and Computer Graphics. Theory and Applications. VISIGRAPP 2011. Communications in Computer and Information Science, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32350-8_7

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  • DOI: https://doi.org/10.1007/978-3-642-32350-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32349-2

  • Online ISBN: 978-3-642-32350-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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