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Face Recognition Using Local Binary Patterns Histograms (LBPH) on an FPGA-Based System on Chip (SoC)

机译:在基于FPGA的片上系统(SoC)上使用局部二进制模式直方图(LBPH)进行人脸识别

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The need for facial recognition systems that are fast and accurate is continuously increasing. In this paper, a face recognition implementation on a System on Chip (SoC), integrated with an FPGA, is presented. This implementation utilizes Local Binary Patterns Histograms to extract features from test face images and Manhattan distance to retrieve the correct match from the system's face database. The SoC utilized is a Zynq-7030. The feature extraction and the distance computations, between the database, are implemented on the FPGA. The ARM processor of the SoC is responsible for receiving the input stream and presenting the output result, using the acquired distances. Real-time face recognition, with an execution time of 8.6 ms and accuracy of 79%, is achieved through this implementation.
机译:快速而准确的面部识别系统的需求在不断增长。在本文中,提出了一种在与FPGA集成的片上系统(SoC)上的人脸识别实现。此实现利用局部二进制模式直方图从测试面部图像和曼哈顿距离中提取特征,以从系统的面部数据库中检索正确的匹配项。使用的SoC是Zynq-7030。数据库之间的特征提取和距离计算在FPGA上实现。 SoC的ARM处理器负责使用获取的距离来接收输入流并呈现输出结果。通过此实现,可以实现8.6 ms的执行时间和79%的准确度的实时面部识别。

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