基于并行算法的快速人脸识别系统设计与实现

为了提高人脸识别实时处理速度,并充分利用当前多核处理器资源,文章实现了一种在Python环境下基于并行算法的快速人脸识别系统。人脸特征与数据库的储存实时交互,利用各子程序安全通信实现同步处理,并行处理实时人脸检测和人脸特征编码提取,同时进行最相似人脸匹配。实验结果表明,程序并行后有着速度快、准确度高、实时性强等优点。为大数据人脸识别处理提供了方法,也有利于实际的使用。

Design and implementation of fast face recognition system based on parallel algorithm

In order to improve the real-time processing speed of face recognition and make full use of the current multi-core processor resources,this paper implements a fast face recognition system based on parallel algorithms in Python.The facial features are stored and interacted with the database in real time.The subroutines are used to securely communicate with each other in parallel.Real-time face detection and facial feature code extraction are processed in parallel.Similar face matching.At the same time,the program was improved so that it can handle multiple source data.The experimental results show that the parallel program has the advantages of fast speed,high accuracy,high stability,good recognition effect,and strong real-time performance.It provides a method for face recognition processing in big data and is also beneficial to practical use.