基于Hadoop云计算环境下人脸识别系统的研究与实现
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摘要
为了满足时代数据处理的处理,人脸识别系统作为传统模式识别的课题要进行创新,为了适应此变化,就实现了基于Hadoop云计算环境中的人脸识别系统研究和实现。首先,对人脸识别系统的设计需求进行了分析,实现基于云计算环境人脸识别系统的总体设计。然后,对人脸识别系统的硬件平台进行设计。之后,对人脸识别系统的软件模块进行设计。最后,对设计的基于云计算环境人脸识别系统进行测试。通过测试结果表示,所设计的人脸识别系统识别精准率比传统识别率要高,并且人脸识别效果要优于传统系统。
In order to meet the processing of data processing in the times,face recognition system should be innovated as the subject of traditional pattern recognition. In order to adapt to this change,the research and implementation of face recognition system based on Hadoop cloud computing environment is realized. First,the design requirements of face recognition system are analyzed,and the overall design of face recognition system based on cloud computing environment is realized. Then,the hardware platform of the face recognition system is designed. After that,the software module of the face recognition system is designed. Finally,the face recognition system based on cloud computing environment is tested. The test results show that the recognition accuracy of the designed face recognition system is higher than that of the traditional recognition rate,and the effect of face recognition is better than that of the traditional system.
In order to meet the processing of data processing in the times,face recognition system should be innovated as the subject of traditional pattern recognition. In order to adapt to this change,the research and implementation of face recognition system based on Hadoop cloud computing environment is realized. First,the design requirements of face recognition system are analyzed,and the overall design of face recognition system based on cloud computing environment is realized. Then,the hardware platform of the face recognition system is designed. After that,the software module of the face recognition system is designed. Finally,the face recognition system based on cloud computing environment is tested. The test results show that the recognition accuracy of the designed face recognition system is higher than that of the traditional recognition rate,and the effect of face recognition is better than that of the traditional system.
引文
[1]李朋飞.基于Hadoop平台失踪人口检索系统设计与实现[D].郑州:郑州大学,2014.
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[16]商莹,付安英,袁战军.基于ZigBee的人脸识别智能监控系统的研究[J].电子设计工程,2017,25(11):107-110.
[2]余征.基于Hadoop的人脸图像识别并行处理方法研究与实现[D].成都:西南交通大学,2015.
[3]吕联盟.基于云计算的人脸识别系统研究与设计[D].西安:长安大学,2014.
[4]刘晓玲,陈云海,林立宇,等.人脸识别服务云计算化技术方案分析[J].广东通信技术,2016,12(1):14-17.
[5]马博宇,尉寅玮.基于AdaBoost算法的人脸识别系统的研究与实现[J].仪器仪表学报,2016,14(s1):162-167.
[6]杨昆澎.基于眼球跟踪的活体检测人脸识别系统研究与实现[D].济南:济南大学,2017.
[7]刘凯伦.视频监控中实时人脸识别系统的研究与实现[D].郑州:郑州大学,2017.
[8]毛睿.基于小波和PCA的人脸识别系统的研究与实现[J].科技广场,2017,15(8):6-12.
[9]茹峰.基于ARM嵌入式平台的人脸识别系统的研究与实现[D].北京:北京工业大学,2016.
[10]陆娇蓝,陈军,杨著.基于云计算的嵌入式人脸识别系统建构与研究[J].计算机测量与控制,2016,24(4):146-148.
[11]徐伸杰.基于改进的LTP的人脸识别系统研究及实现[D].杭州:杭州电子科技大学,2016.
[12]任玉强,田国栋,周祥东,等.高安全性人脸识别系统中的唇语识别算法研究[J].计算机应用研究,2017,34(4):1221-1225.
[13]郭中华,苑俊英,伍冯洁,等.基于OpenCV的人脸识别系统的研究[J].电子世界,2016,21(18):105-106.
[14]霍妍,李长明.基于人脸识别考勤系统的设计与实现[J].通化师范学院学报,2016,37(12):1-3.
[15]孙琛.基于嵌入式系统的人脸识别技术研究及实现[J].中国新通信,2017,19(8):89-89.
[16]商莹,付安英,袁战军.基于ZigBee的人脸识别智能监控系统的研究[J].电子设计工程,2017,25(11):107-110.