Abstract
It is known that fixed thresholds mostly fail in two situations as they only search for a certain skin color range: (i) any skin-like object may be classified as skin if skin-like colors belong to fixed threshold range. (ii) any true skin for different races may be mistakenly classified as non-skin if that skin colors do not belong to fixed threshold range. In this paper, a dynamic threshold of different skin colors based on the input image is determined by the combination of graph cuts (GC) and probability neural network (PNN). The compared results among GC, PNN and GC+PNN are presented not only to verify the accurate segmentation of different skin colors but also to reduce the computation time as compared with only using the neural network for the classification of different skin-colors and non-skin-color. In addition, the experimental results for different lighting conditions confirm the usefulness of the proposed methodology.
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References
Kakumanu, P., Makrogiannis, S., Bourbakis, N.: A Survey of Skin-Color Modeling and Detection Methods. Pattern Recognition, 1106–1122 (2007)
Liensberger, C., Stöttinger, J., Kampel, M.: Color-Based and Context-Aware Skin Detection for Online Video Annotation. In: IEEE International Workshop on Multimedia Signal Processing, MMSP 2009, Rio De Janeiro, pp. 1–6 (2009)
Cao, X.Y., Liu, H.F., Zou, Y.Y.: Gesture Segmentation Based on Monocular Vision Using Skin Color and Motion Cues. In: IEEE International Conference on Image Analysis and Signal Processing, Zhejiang China, pp. 358–362 (2010)
Yogarajah, P., Condell, J., Curran, K., Cheddad, A., McKevitt, P.: A Dynamic Threshold Approach for Skin Segmentation in Color Images. In: IEEE 17th International Conference on Image Processing, Hong Kong, pp. 2225–2228 (2010)
Veredas, F., Mesa, H., Morente, L.: Binary Tissue Classification on Wound Images Neural Networks and Bayesian Classifiers. IEEE Trans. Medical Imaging 29(2), 410–427 (2010)
Tsai, C.M., Yeh, Z.M.: Contrast Compensation by Fuzzy Classification and Image Illumination Analysis for Back-lit and Front-lit Color Face Images. IEEE Trans. Consumer Electronics 56(3), 1570–1578 (2010)
Sun, M., Liu, Z., Qiu, J., Zhang, Z., Sinclair, M.: Active Lighting for Video Conferencing. IEEE Trans. Cir. and Syst. for Video Technol. 19(12), 1819–1823 (2009)
Wang, Z.G., Liu, C.L.: A Method of Dynamic Skin Color Correction Applied to Display Devices. IEEE Trans. Consumer Electronics 55(3), 967–972 (2009)
Tao, W., Jin, H., Zhang, Y., Liu, L., Wang, D.: Image Threshold Using Graph Cuts. IEEE Trans. Syst. Man & Cybern., Pt. C 38(5), 1181–1195 (2008)
Psyllos, A., Anagnostopoulos, C.N., Kayafas, E.: Vehicle Model Recognition from Frontal View Image Measurements. Computer Standards & Interfaces 33, 142–151 (2011)
Sonka, M., Hiavac, V., Boyle, R.: Image Processing, Analysis, and Machine Vision, 3rd edn. Cengage Learning. (2008)
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Hwang, CL., Lu, KD. (2011). The Segmentation of Different Skin Colors Using the Combination of Graph Cuts and Probability Neural Network. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_4
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DOI: https://doi.org/10.1007/978-3-642-21498-1_4
Publisher Name: Springer, Berlin, Heidelberg
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