Fast face detection via morphology-based pre-processing
An efficient face detection algorithm which can detect multiple faces in cluttered environment is proposed. First of all, morphological operations and labeling process were performed to obtain the eye-analogue segments. Based on some matching rules and the geometrical relationship on a face, eye-analogue segments were grouped into pairs and used to locate potential face regions. Finally, the potential face regions were verified via a trained neural network and the true faces were determined by optimizing a distance function. Since the morphology-based eye-analogue segmentation process can efficiently locate the potential eye-analogue regions, the subsequent processing only has to deal with 5–10% area of the original image. Experiments demonstrate that an approximately 94% success rate is reached and the relative false detection rate is very low.
Key WordsFace Detection Morphological Opening/Closing Operation
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