Separability Analysis of Color Classes on Dermoscopic Images

  • Cátia S. P. Silva
  • André R. S. Marcal
  • Marta A. Pereira
  • Teresa Mendonça
  • Jorge Rozeira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7325)


Dermoscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions used in dermatology. There is currently a great interest in the prospects of automatic image analysis methods for dermoscopy, both to provide quantitative information about a lesion, which can be of relevance for the clinician, and as a stand alone early warning tool. The standard approach in automatic dermoscopic image analysis has usually three stages: (i) segmentation, (ii) feature extraction and selection, (iii) lesion classification. This paper evaluates the potential of an alternative approach based on the Menzies method - presence of 1 or more of 6 color classes, indicating that the lesion should be considered a potential melanoma. This method does not require stages (i) and (ii) - lesion segmentation and feature extraction. The Jeffries-Matusita and Transformed Divergence metrics were used to evaluate the color class separability. The preliminary results presented in this paper suggest that a system based on the Menzies method could provide valuable information for automatic dermoscopic image analysis.


Dermoscopy Menzies method separability analysis Jeffries-Matusita Tranformed Divergence 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Silveira, M., Nascimento, J.C., Marques, J.S., Marçal, A.R.S., Mendonça, T., Yamauchi, S., Maeda, J., Rozeira, J.: Comparison of Segmentation Methods for Melanoma Diagnosis in Dermoscopy Images. IEEE Journal of Selected Topics in Signal Processing 3(1), 35–45 (2009)CrossRefGoogle Scholar
  2. 2.
    McGovern, T.W., Litaker, M.S.: Clinical predictors of malignant pigmented lesions: a comparison of Glasgow seven-point checklist and the American Cancer Society’s ABCDs of pigmented lesions. J. Dermatol. Surg. Oncol. 18, 22–26 (1992)Google Scholar
  3. 3.
    du Vivier, A.W., Williams, H.C., Brett, J.V., Higgins, H.M.: How do malignant melanomas present and does this correlate with the seven-point checklist? Clin. Exp. Dermatol. 16, 344–347 (1991)CrossRefGoogle Scholar
  4. 4.
  5. 5.
    Pehamberger, H., Binder, M., Steiner, A., Wolff, K.: In vivo epiluminescence microscopy: improvement of early diagnosis of melanoma. J. Investig. Dermatol. 100, 356–362 (1993)CrossRefGoogle Scholar
  6. 6.
    Menzies, S.W.: A method for the diagnosis of primary cutaneous melanoma using surface microscopy. Derm. Clinics. 19(2), 299–305 (2001)CrossRefGoogle Scholar
  7. 7.
    van der Heijden, F., Duin, R.P.W., Ridder, D., Tax, D.M.J.: Classification, Parameter Estimation and State Estimation - An Engineering Approach using Matlab. Wiley (2004)Google Scholar
  8. 8.
    Richards, J.A., Jia, X.: Remote Sensing Digital Image Analysis: An Introduction, 4th edn. Springer (2006)Google Scholar
  9. 9.
    Kailath, T.: The divergence and Bhattacharyya distance measures in signal selection. IEEE Transactions Communication Technology 15(1), 52–60 (1967)CrossRefGoogle Scholar
  10. 10.
    Kullback, S., Burnham, K.P., Laubscher, N.F., Dallal, G.E., Wilkinson, L., Morrison, D.F., Loyer, M.W., Eisenberg, B., et al.: Letter to the Editor: The Kullback Leibler distance. Am. Stat. 41(4), 340–341 (1987)Google Scholar
  11. 11.
    Reyes-Aldasoro, C.C., Bhalerao, A.: The Bhattacharyya space for feature selection and its application to texture segmentation. Patt. Recog. Soc. 39, 812–826 (2006)zbMATHCrossRefGoogle Scholar
  12. 12.
    Sousa, B.F.S., Teixeira, A.S., Silva, F.A.T.F., Andrade, E.M., Braga, A.P.S.: Evaluation of Classifiers Based on Machines Learning to Land Use and Cover Classification on Caatinga Biome. Braz. J. Cartog. 62(2), 385–399 (2010)Google Scholar
  13. 13.
    Kolmogorov, A.: Sulla determinazione empirica di una legge di distributione. Giornale dell Istituto Italiano degli Attuari 4, 83–91 (1993)Google Scholar
  14. 14.
  15. 15.
    de Giorgi, V., Trez, E., Salvini, C., Duquia, R., De Villa, D., Sestini, S., Gervini, R., Lotti, T.: Dermoscopy in black people. Brit. J. Dermatol. 155, 695–699 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Cátia S. P. Silva
    • 1
  • André R. S. Marcal
    • 2
  • Marta A. Pereira
    • 3
  • Teresa Mendonça
    • 2
  • Jorge Rozeira
    • 3
  1. 1.Faculdade de Engenharia, Dep. Engenharia Eletrotécnica e de ComputadoresUniv. PortoPortoPortugal
  2. 2.Faculdade de Ciências, Dep. MatemáticaUniv. PortoPortoPortugal
  3. 3.Servicco de DermatologiaHospital Pedro HispanoSenhora da HoraPortugal

Personalised recommendations