A Bag-of-Features Approach for the Classification of Melanomas in Dermoscopy Images: The Role of Color and Texture Descriptors

  • Catarina Barata
  • Margarida Ruela
  • Teresa Mendonça
  • Jorge S. Marques
Part of the Series in BioEngineering book series (SERBIOENG)


The identification of melanomas in dermoscopy images is still an up to date challenge. Several Computer Aided-Diagnosis Systems for the early diagnosis of melanomas have been proposed in the last two decades. This chapter presents an approach to diagnose melanomas using Bag-of-features, a classification method based on a local description of the image in small patches. Moreover, a comparison between color and texture descriptors is performed in order to assess their discriminative power. The presented results show that local descriptors allow an accurate representation of dermoscopy images and achieve good classification scores: Sensitivity \(=\) 93 % and Specificity \(=\) 88 %. Furthermore it shows that color descriptors perform better than texture ones in the detection of melanomas.


Melanoma diagnosis Dermoscopy Bag-of-features  Feature extraction Feature analysis Color features  Texture features 



The authors thank to Dr. Jorge Rozeira for providing the dermoscopy images. This work was supported by Fundação Ciência e Tecnologia in the scope of the grant SFRH/BD/84658/2012 and projects PTDC/SAU-BEB/103471/2008 and PEst-OE/EEI/LA0009/2011.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Catarina Barata
    • 1
  • Margarida Ruela
    • 1
  • Teresa Mendonça
    • 2
  • Jorge S. Marques
    • 1
  1. 1.Institute for Systems and RoboticsInstituto Superior TécnicoLisboaPortugal
  2. 2.Faculdade de Ciências da Universidade do PortoPortoPortugal

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