Abstract
Comparative test classification performance of machine learning model classifiers in skin segmentation using entire and sub-feature spaces is studied and presented. The effects of features on classification performance is demonstrated via test performance of classifiers trained on feature spaces and subsets. Model validation is assessed.
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
References
Phung, S.L., Bouzerdoum, A., Chai, D.: Skin segmentation using color pixel classification: analysis and comparison. IEEE Trans. Pattern Anal. Mach. Intell. 27(1), 148–154 (2005)
Saini, H.K., Chand, O.: Skin segmentation using RGB color model and implementation of switching conditions. Skin 3(1), 1781–1787 (2013)
Kolkur, S., Kalbande, D., Shimpi, P., Bapat, C., Jatakia, J.: Human skin detection using RGB, HSV and YCbCr color models. arXiv preprint arXiv:1708.02694 (2017)
Bhatt, R.B., Dhall, A., Sharma, G., Chaudhury, S.: Efficient skin region segmentation using low complexity fuzzy decision tree model. In: India Conference IEEE-INDICON, pp. 1–4 (2009)
Khan, R., Hanbury, A., Stöttinger, J.: Skin detection: a random forest approach. In: 17th IEEE International Conference on Image Processing, pp. 4613–4616 (2010)
Esteva, A., Kuprel, B., Novoa, R.A., Ko, J., Swetter, S.M., Blau, H.M., Thrun, S.: Dermatologist-level classification of skin cancer with deep neural networks. Nature 542(7639), 115 (2017)
Shaik, K.B., Ganesan, P., Kalist, V., Sathish, B.S., Jenitha, J.M.M.: Comparative study of skin color detection and segmentation in HSV and YCbCr color space. Procedia Comput. Sci. 57, 41–48 (2015)
Vezhnevets, V., Sazonov, V., Andreeva, A.: A survey on pixel-based skin color detection techniques. Proc. Graph. 3, 85–92 (2003)
Khan, R., Hanbury, A., Stöttinger, J., Bais, A.: Color based skin classification. Pattern Recogn. Lett. 33(2), 157–163 (2012)
Nisar, H., Ch’ng, Y.K., Chew, T.Y. , Yap, V.V., Yeap, K.H., Tang, J.J.: A color space study for skin lesion segmentation. In: IEEE International Conference on Circuits and Systems, pp. 172-176 (2013)
Garnavi, R., Aldeen, M., Celebi, M.E., Bhuiyan, A., Dolianitis, C., Varigos, G.: Automatic segmentation of dermoscopy images using histogram thresholding on optimal color channels. Int. J. Med. Med. Sci. 1(2), 126–134 (2010)
A-iyeh, E., Peters, J.F.: Gini Index-based digital image complementing in the study of medical images. J. Intell. Decis. Technol. 9(2), 209–218 (2015)
Acknowledgment
I thank the anonymous reviewers for their feedback that led to improvements. Last but not least I thank God Almighty and my family.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
A-iyeh, E. (2020). Comparative Feature-Ranking Performance of Machine Learning: Model Classifiers in Skin Segmentation and Classification. In: Arai, K., Kapoor, S. (eds) Advances in Computer Vision. CVC 2019. Advances in Intelligent Systems and Computing, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-17798-0_48
Download citation
DOI: https://doi.org/10.1007/978-3-030-17798-0_48
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-17797-3
Online ISBN: 978-3-030-17798-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)