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首页> 外文会议>Second IEEE Pacific Rim Conference on Multimedia, Oct 24-26, 2001, Beijing, China >Automatic Human Face Recognition System Using Fractal Dimension and Modified Hausdorff Distance
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Automatic Human Face Recognition System Using Fractal Dimension and Modified Hausdorff Distance

机译：分形维和修正的Hausdorff距离的人脸自动识别系统

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摘要

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.
机译：本文提出了一种高效的人脸自动识别系统。分形维数是纹理的有效表示，用于将眼睛定位在人脸中。我们提出一种改进的方法来估计分形维数，该分形维数对光照条件不太敏感，并提供有关所考虑图像方向的信息。根据眼睛的位置，将两个面部图像进行归一化，对齐，然后通过新的改进的Hausdorff距离度量进行比较。由于不同的脸部区域对于脸部识别的重要性不同，因此根据从人脸的空间信息得出的加权函数对修正的Hausdorff距离进行加权。实验结果表明，我们的方法对于第一个，前五个，前十个可能匹配的脸部分别达到76％，84％和92％的识别率。如果手动选择眼睛的位置，则相应的识别率分别为82％，95％和98％。用于检测眼睛和识别人脸的平均处理时间少于两秒钟。

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