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Decoding Color Structured Light Patterns with a Region Adjacency Graph

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Pattern Recognition (DAGM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5748))

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Abstract

We present a new technique for decoding color stripe or color checkerboard patterns as often used for single-shot 3d range data acquisition with structured light. The key idea is to segment the camera image into superpixels with a watershed transform. We then describe a new algorithm that constructs a regions adjacency graph and uses it to solve the correspondence problem. This is an improvement over existing scanline based evaluation methods as the spatial coherence assumption can be relaxed. It allows to measure non-smooth objects that have so far posed problems for single-shot acquisition. The algorithm works in near real time even in uncontrolled environments. Experimental results are given.

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Author information

Authors and Affiliations

  1. Siemens AG, CT PS 9, Otto-Hahn-Ring 6, 81739, Munich, Germany

    Christoph Schmalz

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  1. Christoph Schmalz
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Editors and Affiliations

  1. Digitale Bildverarbeitung, Universität Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany

    Joachim Denzler  & Herbert Süße  & 

  2. Fraunhofer-Institut für Angewandte Optik und Feinmechanik, Albert-Einstein-Str. 7, 07745, Jena, Germany

    Gunther Notni

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Schmalz, C. (2009). Decoding Color Structured Light Patterns with a Region Adjacency Graph. In: Denzler, J., Notni, G., Süße, H. (eds) Pattern Recognition. DAGM 2009. Lecture Notes in Computer Science, vol 5748. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03798-6_47

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  • DOI: https://doi.org/10.1007/978-3-642-03798-6_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03797-9

  • Online ISBN: 978-3-642-03798-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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