| Summary: | 碩士 === 義守大學 === 電機工程學系 === 103 === For the purposes of facial recognition, in this thesis, we design and implement an embedded system whose platform consists of pcDuono-V2 board with ARM-processor inside and a Linux-kernel-based operating system, Ubuntu. A camera is set up on the platform to take human face pictures, and a program is used to recognize these pictures via biological multi-features. The corresponding facial recognition program running on the embedded system is based on Haar-like features and AdaBoost algorithm. Haar-like features are the foundation of recognition, while AdaBoost is a machine learning algorithm for training classifiers. According to the experimental results, the resultant embedded system can recognize the experimental subjects during one second in every our considered situations, which ensures the real-time performance.
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