Error-Tolerant Content-Based Music-Retrieval with Mathematical Morphology

  • Mikko Karvonen
  • Mika Laitinen
  • Kjell Lemström
  • Juho Vikman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6684)


In this paper, we show how to apply the framework of mathematical morphology (MM) in order to improve error-tolerance in content-based music retrieval (CBMR) when dealing with approximate retrieval of polyphonic, symbolically encoded music. To this end, we introduce two algorithms based on the MM framework and carry out experiments to compare their performance against well-known algorithms earlier developed for CBMR problems. Although, according to our experiments, the new algorithms do not perform quite as well as the rivaling algorithms in a typical query setting, they provide ease of adjusting the desired error tolerance. Moreover, in certain settings the new algorithms become even faster than their existing counterparts.


MIR music information retrieval mathematical morphology geometric music retrieval digital image processing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mikko Karvonen
    • 1
  • Mika Laitinen
    • 1
  • Kjell Lemström
    • 1
  • Juho Vikman
    • 1
  1. 1.Department of Computer ScienceUniversity of HelsinkiFinland

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