System for Reading Braille Embossed on Beverage Can Lids for Authentication

  • Trine Kirkhus
  • Jens T Thielemann
  • Britta Fismen
  • Henrik Schumann-Olsen
  • Ronald Sivertsen
  • Mats Carlin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)


The paper describes a system for reading embossed Braille patterns on used aluminum beverage container lids. The intent of the system is to check whether the used containers are entitled to a refund. The lids have strong specular reflections. The reflections are avoided by a novel method that illuminates the lid alternating from two angles, and acquires two separate images. This illumination method is more compact than existing methods. We use the extended maxima algorithm to detect the Braille dots, and a cluster-based pattern point matching algorithm to recognize a pre-defined Braille pattern. The algorithms are customized to increase speed using a priori information. The system was evaluated on a test set containing 225 images. The median time used for analyzing one beverage can was 1 second, and the recognition rate was 94 percent.


Recognition Rate Affine Transformation Reference Pattern Illumination Source Image Acquisition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Trine Kirkhus
    • 1
  • Jens T Thielemann
    • 1
  • Britta Fismen
    • 1
  • Henrik Schumann-Olsen
    • 1
  • Ronald Sivertsen
    • 2
  • Mats Carlin
    • 3
  1. 1.SINTEFBlindern, OsloNorway
  2. 2.Tomra Systems ASAAsker
  3. 3.Carlin’s Algorithm FactoryGjettum

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