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Wood Veneer Species Recognition Using Markovian Textural Features

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Computer Analysis of Images and Patterns (CAIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9256))

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Abstract

A mobile Android application that can automatically recognize wood species from a low quality mobile phone photo under varying illumination conditions is presented. The wood recognition is based on the Markovian, spectral, and illumination invariant textural features. The method performance was verified on a wood database, which contains veneers from sixty-six varied European and exotic wood species. The Markovian features improvement of the correct wood recognition rate is about 40% compared to the best alternative - the Local Binary Patterns features.

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Authors and Affiliations

  1. The Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic

    Michal Haindl & Pavel Vácha

Authors
  1. Michal Haindl
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  2. Pavel Vácha
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Corresponding author

Correspondence to Michal Haindl .

Editor information

Editors and Affiliations

  1. University of Malta, Msida, Malta

    George Azzopardi

  2. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

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Haindl, M., Vácha, P. (2015). Wood Veneer Species Recognition Using Markovian Textural Features. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_25

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  • DOI: https://doi.org/10.1007/978-3-319-23192-1_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23191-4

  • Online ISBN: 978-3-319-23192-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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