Low-cost face recognition system

• Main Authors: Shih-Rong Wang, 王仕融
• Other Authors: WEI-YU HAN
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/qu53ce

碩士 === 健行科技大學 === 資訊工程系碩士班 === 106 === Face recognition is one of the most widely used information security management solutions in today. Usually face recognition system includes image capture, face area capture, face feature vector calculation, training and construction of face feature vector database, and finally face recognition. In general applications, higher hardware performance requirements are needed to quickly extract and analyze face features. Therefore, it is more difficult for low-end hardware devices to achieve face recognition applications such as access control. This study uses the free face recognition service provided by Microsoft to send face photos to the cloud platform through the Internet, and calculates and obtains face feature vectors, reducing the need for large and complex photo processing loading. Therefore, the Raspberry Pi can be used as the terminal hardware device realizes the functions required by the face recognition system. The entire system hardwire consists of the Raspberry Pi 3, Raspberry Pi Camera Module, and network devices. The software include Raspbian OS, Python 3.0, and OpenCV as the development language. Implementation system function include face capture, network control for using Microsoft facial recognition services, face feature extraction and analysis, face feature vector database construction and face recognition and access control management applications; to achieve machine learning required data collection, training, testing and actual use.