An edge-based face detection algorithm robust against illumination, focus, and scale variations
作者： Tadashi Shibata , Yasufumi Suzuki
DOI: 10.5281/ZENODO.38646
关键词: Signal processing 、 Facial recognition system 、 Artificial intelligence 、 Feature extraction 、 High density 、 Computer vision 、 Biometrics 、 Pattern recognition 、 Face detection 、 Robustness (computer science) 、 Mathematics 、 Edge detection
摘要: A face detection algorithm very robust against illumination, focus and scale variations in input images has been developed based on the edge-based image representation. The multiple-clue our previous work [1] employed conjunction with a new decision criterion called “density rule,” where only high density clusters of detected candidates are retained as faces. As result, occurrence false negatives greatly reduced. robustness circumstance demonstrated.
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