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Detection of Chickenpox Vesicles in Digital Images of Skin Lesions

  • Julián Oyola
  • Virginia Arroyo
  • Ana Ruedin
  • Daniel Acevedo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)

Abstract

Chickenpox is a viral disease characterized by itchy skin vesicles that can have severe complications in adults. A tool for automatic detection of these lesions in patients’ photographs is highly desirable to help the physician in the diagnosis. In this work we design a method for detection of chickenpox skin lesions in images. It is a combination of image processing techniques - color transform, equalization, edge detection, circular Hough transform- and statistical tests. We obtain highly satisfactory results in the detection of chickenpox vesicles, the elimination of false detections using the Kullback Leibler divergence, and in preliminary tests for discrimination between chickenpox and herpes zoster.

Keywords

skin lesions chickenpox detection image processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Julián Oyola
    • 1
  • Virginia Arroyo
    • 1
  • Ana Ruedin
    • 1
  • Daniel Acevedo
    • 1
  1. 1.Departamento de Computación, Facultad de Ciencias Exactas y NaturalesUniversidad de Buenos AiresCiudad de Buenos AiresArgentina

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