Face detection is an important problem considered in many applications. To analyze the information included in face images, a robust and efficient face detection algorithm is required. The face detection in a complex background is still more difficult. In the present paper, our objective is to propose a novel fuzzy geometric face model for single as well as multiple face detection using a skin color fusion model. We combine the skin region extraction using different color spaces, namely, RGB, YCbCr and HSI, and face detection using fuzzy based geometric face model into a robust face detection system. The skin color fusion model is used to segment the skin color region in a face image. Then, in each of the skin regions, the facial features, namely, eyes and mouth, are extracted by using fuzzy geometric face model. The experimentation has been done using several publicly available standard face databases. The experimental results show that the proposed algorithm performs satisfactorily with an average accuracy of 97.40% and is efficient in terms of accuracy and detection time in comparison with the state-of-the-art methods in the literature. © 2013 Springer.
CITATION STYLE
Hiremath, P. S., & Hiremath, M. (2013). Fuzzy geometric face model for face detection based on skin color fusion model. In Advances in Intelligent Systems and Computing (Vol. 174 AISC, pp. 977–982). Springer Verlag. https://doi.org/10.1007/978-81-322-0740-5_118
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