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Fast face detection via morphology-based pre-processing
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DOI：10.1016/S0031-3203(99)00141-7.png)
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摘要
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An efficient face detection algorithm which can detect multiple faces oriented in any directions in a cluttered environment is proposed. In this paper, a morphology-based technique is first devised to perform eye-analogue segmentation. Next, the previously located eye-analogue segments are used as guides to search For potential face regions. Then, each of these potential face images is normalized to a standard size and fed into a trained backpropagation neural network for identification. In this detection system, the morphology-based eye-analogue segmentation process is able to reduce the background part of a cluttered image by up to 95%. This process significantly speeds up the subsequent face detection procedure because only 5-10% of the regions of the original image remain for further processing. Experiments demonstrate that an approximately 94% success rate is reached, and that the relative False detection rate is very low. (C) 2000 Published by Elsevier Science Ltd on behalf of Pattern Recognition Society.
Keyword:
face detection
backpropagation neural network
morphological opening/closing operation
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IF:
7.6
论文数:
1.3W
被引数:
4.5W
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Facial feature detection using geometrical face model: An efficient approach.png)
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