A Novel Piece-Wise Linear Algorithm for Human Skin Segmentation

Abstract:

This paper presents a novel method for skin segmentation in color images using piece-wise linear bound skin detection. Various color schemes are investigated and evaluated to find the effect of color space transformation over the skin detection performance. The comprehensive knowledge about the various color spaces helps in skin color modeling evaluation. The absence of the luminance component increases performance, which also supports in finding the appropriate color space for skin detection. The single color component produces the better performance than combined color component and reduces computational complexity.

• Periodical: Applied Mechanics and Materials (Volume 743)
• Pages: 317-320
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.743.317
• Online since: March 2015
• Authors: Ravi Subban, Pasupathi Perumalsamy, G. Annalakshmi
• Keywords: Luminance, Piecewise, Segmentation, Skin Detection, Threshold, Transformation

References

[1] Ravi Subban, Muthukumar Subramanyam, Pasupathi P et al, A Review on Face Detection Approaches, Advances in Communication, Network, and Computing, CNC Elsevier, (2014).

[2] Muthukumar Subramanyam, Krishnan Nallaperumal, Ravi Subban, Pasupathi P, Shashikala, S. Selvakumar, S. Gayathri, Real-Time Hard and Soft Shadow Compensation with Adaptive Patch Gradient Pairs, Advance in SP DOI: 10. 1007/978-3-04960-1-22, 2014, Springer International Publishing Switerland (2014).

DOI: 10.1007/978-3-319-04960-1_22

[3] Michal Kawulok, et al, Spatial based skin detection using discriminative skin presence features, Elsevier, (2013).

[4] Rehanullah Khan, et al, Multiple color space channel fusion for skin detection, Springer, (2013).

[5] L U Wan and HUANG Jie, Skin Detection Method Based on Cascaded AdaBoost Classifier, Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg, 17(2): 197-202 DOI: 10. 1007/s12204-012-1252-6, (2012).

DOI: 10.1007/s12204-012-1252-6

[6] Shah Mostafa Khaled, et al, Combinatorial Color Space Models for Skin Detection in Sub-continental Human Images, IVIC 2009, LNCS 5857, p.532–542, 2009. © Springer-Verlag Berlin Heidelberg (2009).

[7] Kakumanu P., et al, A survey of skin-color modeling and detection methods, PR 40, 1106–1122, (2007).

[8] Schmugge S. J, , et al, Objective evaluation of approaches of skin detection using ROC analysis, Computer Vision and Image Understanding 108, 41–51 Mathias Wimmer, Bernd Rading, (2006).

DOI: 10.1016/j.cviu.2006.10.009

[9] Sanjay Kr Singh, and D.S. Chauhan, Mayank Vasta Richa Singh, A robust Skin color Based Face detection Algorithm, in Tamkang Journal of Science and Engineering, Vol. 6, No. 4, pp.227-234, (2003).

[10] Hsu R. -L, et al, Face detection in color images, IEEE. Trans. Pattern. Anal. Mach. Intel. 24(5), 696–706 (2002).

[11] Jones M. J and Rehg J. M, Statistical color models with application to skin detection, Int. Journal of Computer Vision. 46(1), 81–96, (2002).

[12] T. Gevers A. W. M. Smeulders and PickToSeek, Combining Color and Shape Invariant Features for Image Retrieval, IEEE Transactions on Image Processing, 9 (1): 102–119, (2000).

DOI: 10.1109/83.817602

[13] Brand J and Mason J, A Comparative Assessment of three Approaches to Pixel Level Human Skin-Detection, In: Proc. of Intl. Conf. on Pattern Recognition, vol. 1, p.1056–1059, (2000).

DOI: 10.1109/icpr.2000.905653