Evaluating Shape Descriptors for Detection of Maya Hieroglyphs

  • Edgar Roman-Rangel
  • Jean-Marc Odobez
  • Daniel Gatica-Perez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7914)


In this work we address the problem of detecting instances of complex shapes in binary images. We investigated the effects of combining DoG and Harris-Laplace interest points with SIFT and HOOSC descriptors. Also, we propose the use of a retrieval-based detection framework suitable to deal with images that are sparsely annotated, and where the objects of interest are very small in proportion to the total size of the image. Our initial results suggest that corner structures are suitable points to compute local descriptors for binary images, although there is the need for better methods to estimate their appropriate characteristic scale when used on binary images.


Shape detection image retrieval Maya hieroglyphs 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Edgar Roman-Rangel
    • 1
  • Jean-Marc Odobez
    • 2
    • 3
  • Daniel Gatica-Perez
    • 2
    • 3
  1. 1.University of GenevaSwitzerland
  2. 2.Idiap Research InstituteSwitzerland
  3. 3.École Polytechnique Fédérale de Lausanne (EPFL)Switzerland

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