Abstract
In this paper, an efficient automatic human face recognition system is proposed. Fractal dimension is an efficient representation of texture which is used to locate the eyes in a human face. We propose a modified approach to estimate the fractal dimensions which is less sensitive to lighting conditions and provides information about the orientation of an image under consideration. Based on the position of the eyes, two face images are normalized, aligned and then compared by a new modified Hausdorff distance measure. As different facial regions have different degrees of importance for face recognition, the modified Hausdorff distance is weighted according to a weighted function derived from the spatial information of the human face. Experimental results show that our approach can achieve recognition rates of 76%, 84%, and 92% for the first one, the first five, first ten likely matched faces, respectively. If the position of the eyes is selected manually, the corresponding recognition rates are 82%, 95% and 98%, respectively. The average processing time for detecting the eyes and recognize a human face is less than two seconds.
This work is supported by HKPoIyU research grant G-V498
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© 2001 Springer-Verlag Berlin Heidelherg
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Lin, KH., Guo, B., Lam, KM., Siu, WC. (2001). Automatic Human Face Recognition System Using Fractal Dimension and Modified Hausdorff Distance. In: Shum, HY., Liao, M., Chang, SF. (eds) Advances in Multimedia Information Processing — PCM 2001. PCM 2001. Lecture Notes in Computer Science, vol 2195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45453-5_36
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DOI: https://doi.org/10.1007/3-540-45453-5_36
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