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)


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.


skin lesions chickenpox detection image processing 


  1. 1.
    Yeganeh, H., Ziaei, A., Rezaie, A.: A novel approach for contrast enhancement based on Histogram Equalization. In: IEEE Int. Conf. Computer and Communication Eng., pp. 256–260 (2008)Google Scholar
  2. 2.
    Peng, Z.-Y., Zhu, Y.-H., Zhou, Y.: Real-time Facial Expression Recognition Based on Adaptive Canny Operator Edge Detection. In: IEEE Int. Conf. Multimedia and Information Technology, pp. 154–157 (2010)Google Scholar
  3. 3.
    Rizon, M., Yazid, H., Saad, P., Md Shakaff, A., Saad, A., Sugisaka, M., Yaacob, S., Mamat, M., Karthigayan, M.: Object Detection using Circular Hough Transform. American Journal of Applied Sciences 2(12), 1606–1609 (2005)CrossRefGoogle Scholar
  4. 4.
    Coll, L., Chinchilla, D., Coll, C., Stengel, F., Cabo, H.: Análisis digital de imágenes en lesiones pigmentadas de la piel. Diagnóstico precoz del melanoma. Dermatología Argentina 14(3) (2008)Google Scholar
  5. 5.
    Canny, J.F.: A Computational Approach to Edge Detection. IEEE PAMI 8(6), 679–698 (1986)CrossRefGoogle Scholar
  6. 6.
    Hough, P.V.: Machine analysis of bubble chamber pictures. In: Kowarski, L. (ed.) Int. Conf. on High Energy Accelerators and Instrumentation, pp. 554–556 (1959)Google Scholar
  7. 7.
    Ballard, D.H.: Generalizing the Hough Transform to Detect Arbitrary Shapes. Pattern Recognition 13(2), 111–122 (1981)zbMATHCrossRefGoogle Scholar
  8. 8.
    Pedersen, S.: Circular Hough Transform. Aalborg University, Vision, Graphics, and Interactive Systems (November 2007)Google Scholar

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

Personalised recommendations