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Research on Face Recognition Based on Embedded System

机译:基于嵌入式系统的人脸识别研究

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Because a number of image feature data to store, complex calculation to execute during the face recognition, therefore the face recognition process was realized only by PCs with high performance. In this paper, the OpenCV facial Haar-like features were used to identify face region; the Principal Component Analysis (PCA) was employed in quick extraction of face features and the Euclidean Distance was also adopted in face recognition; as thus, data amount and computational complexity would be reduced effectively in face recognition, and the face recognition could be carried out on embedded platform. Finally, based on Tiny6410 embedded platform, a set of embedded face recognition systems was constructed. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication.
机译:由于要存储大量图像特征数据,因此在人脸识别过程中要执行复杂的计算,因此只有高性能的PC才能实现人脸识别过程。在本文中,使用OpenCV类似于Haar的面部特征来识别面部区域。主成分分析(PCA)用于快速提取人脸特征,欧氏距离也用于人脸识别;这样可以有效减少人脸识别中的数据量和计算复杂度,并且可以在嵌入式平台上进行人脸识别。最后,基于Tiny6410嵌入式平台,构建了一套嵌入式人脸识别系统。测试结果表明,该系统运行稳定,识别率高,可用于便携式和移动式身份验证。

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