Abstract
Dermoscopic images are useful tools towards the diagnosis and classification of skin lesions. One of the first steps to automatically study them is the reduction of noise, which includes bubbles caused by the immersion fluid and skin hair. In this work we provide an effective hair removal algorithm for dermoscopic imagery employing soft color morphology operators able to cope with color images. Our hair removal filter is essentially composed of a morphological curvilinear object detector and a morphological-based inpainting algorithm. Our work is aimed at fulfilling two goals. First, to provide a successful yet efficient hair removal algorithm using the soft color morphology operators. Second, to compare it with other state-of-the-art algorithms and exhibit the good results of our approach, which maintains lesion’s features.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Argenziano, G., Longo, C., Cameron, A., Cavicchini, S., et al.: Blue-black rule: a simple dermoscopic clue to recognize pigmented nodular melanoma. Br. J. Dermatol. 165(6), 1251–1255 (2011)
Baczyński, M., Jayaram, B.: Fuzzy Implications. Studies in Fuzziness and Soft Computing, vol. 231. Springer, Heidelberg (2008)
Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners, vol. 221. Springer, Heidelberg (2007)
Bibiloni, P., González-Hidalgo, M., Massanet, S.: Soft color morphology. In: Submitted to IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017) (2017)
Informe de conclusiones. MELANOMA VISIÓN 360\({}^\circ \): Diálogos entre pacientes y profesionales. Madrid (2015). http://fundacionmasqueideas.org/documentos/. Accessed 20 July 2016
González-Hidalgo, M., Massanet, S., Mir, A., Ruiz-Aguilera, D.: A fuzzy filter for high-density salt and pepper noise removal. In: Bielza, C., Salmerón, A., Alonso-Betanzos, A., Hidalgo, J.I., Martínez, L., Troncoso, A., Corchado, E., Corchado, J.M. (eds.) CAEPIA 2013. LNCS, vol. 8109, pp. 70–79. Springer, Heidelberg (2013). doi:10.1007/978-3-642-40643-0_8
Kerre, E.E., Nachtegael, M.: Fuzzy Techniques in Image Processing. Studies in Fuzziness and Soft Computing, vol. 52. Physica, Heidelberg (2013)
Lee, T., Ng, V., Gallagher, R., Coldman, A., McLean, D.: Dullrazor®: a software approach to hair removal from images. Comput. Biol. Med. 27(6), 533–543 (1997)
Mendonça, T., Ferreira, P.M., Marques, J.S., Marcal, A.R., Rozeira, J.: PH 2 - a dermoscopic image database for research and benchmarking. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5437–5440. IEEE (2013)
Serra, J.: Image Analysis and Mathematical Morphology, vol. 1. Academic Press, Cambridge (1982)
Toossi, M.T.B., Pourreza, H.R., Zare, H., Sigari, M.H., et al.: An effective hair removal algorithm for dermoscopy images. Skin Res. Technol. 19(3), 230–235 (2013)
Zuiderveld, K.: Contrast limited adaptive histogram equalization. In: Graphics GEMS IV, pp. 474–485. Academic Press Professional, Inc. (1994)
Acknowledgments
The Spanish grants TIN 2016-75404-P AEI/FEDER, UE and TIN 2013-42795-P partially supported this work. P. Bibiloni also benefited from the fellowship FPI/1645/2014 of the Conselleria d’Educació, Cultura i Universitats of the Govern de les Illes Balears under an operational program co-financed by the European Social Fund.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Bibiloni, P., González-Hidalgo, M., Massanet, S. (2017). Skin Hair Removal in Dermoscopic Images Using Soft Color Morphology. In: ten Teije, A., Popow, C., Holmes, J., Sacchi, L. (eds) Artificial Intelligence in Medicine. AIME 2017. Lecture Notes in Computer Science(), vol 10259. Springer, Cham. https://doi.org/10.1007/978-3-319-59758-4_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-59758-4_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59757-7
Online ISBN: 978-3-319-59758-4
eBook Packages: Computer ScienceComputer Science (R0)