Music Genre Recognition Using Gabor Filters and LPQ Texture Descriptors

  • Yandre Costa
  • Luiz Oliveira
  • Alessandro Koerich
  • Fabien Gouyon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8259)


This paper presents a novel approach for automatic music genre recognition in the visual domain that uses two texture descriptors. For this, the audio signal is converted into spectrograms and then textural features are extracted from this visual representation. Gabor filters and LPQ texture descriptors were used to capture the spectrogram content. In order to evaluate the performance of local feature extraction, some different zoning mechanisms were taken into account. The experiments were performed on the Latin Music Database. At the end, we have shown that the SVM classifier trained with LPQ is able to achieve a recognition rate above 80%. This rate is among the best results ever presented in the literature.


Music genre texture image processing pattern recognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yandre Costa
    • 1
    • 2
  • Luiz Oliveira
    • 2
  • Alessandro Koerich
    • 2
    • 3
  • Fabien Gouyon
    • 4
  1. 1.State University of Maringá (UEM)MaringáBrazil
  2. 2.Federal University of Paraná (UFPR)CuritibaBrazil
  3. 3.Pontifical Catholic University of Paraná (PUCPR)CuritibaBrazil
  4. 4.Institute for Systems and Computer Engineering of Porto (INESC)PortoPortugal

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