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.
Chapter PDF
Similar content being viewed by others
References
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)
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)
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)
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)
Canny, J.F.: A Computational Approach to Edge Detection. IEEE PAMI 8(6), 679–698 (1986)
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)
Ballard, D.H.: Generalizing the Hough Transform to Detect Arbitrary Shapes. Pattern Recognition 13(2), 111–122 (1981)
Pedersen, S.: Circular Hough Transform. Aalborg University, Vision, Graphics, and Interactive Systems (November 2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Oyola, J., Arroyo, V., Ruedin, A., Acevedo, D. (2012). Detection of Chickenpox Vesicles in Digital Images of Skin Lesions. In: Alvarez, L., Mejail, M., Gomez, L., Jacobo, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2012. Lecture Notes in Computer Science, vol 7441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33275-3_72
Download citation
DOI: https://doi.org/10.1007/978-3-642-33275-3_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33274-6
Online ISBN: 978-3-642-33275-3
eBook Packages: Computer ScienceComputer Science (R0)