摘要
针对传统人脸识别方法在实际应用中存在分别率低,影响识别准确性的问题,开展基于朴素贝叶斯算法的智能电厂监控夜间视频人脸识别方法设计研究。获取智能电厂监控夜间视频图像,利用朴素贝叶斯算法的检测并跟踪人脸,对夜间视频人脸图像进行调优处理,实现了夜间视频人脸识别。通过对比实验证明,此次研究的识别方法分辨率得到有效提升,能够在光照条件和人体姿态条件不理想的情况下,实现对人脸的准确识别。
Aiming at the problem that traditional face recognition methods have low resolution in practical applications and affect the accuracy of recognition,the design and research of smart power plant monitoring night video face recognition methods based on naive Bayes algorithm is carried out.Acquire night video images of smart power plant monitoring,use Naive Bayes algorithm to detect and track human faces,and optimize and process night video face images to realize night video face recognition.Through comparative experiments,it is proved that the resolution of the recognition method in this study has been effectively improved,and it can realize accurate recognition of human faces under conditions of unsatisfactory lighting conditions and human posture conditions.
作者
崔希
刘首明
Cui Xi;Liu Shouming(Jiangxi Province Investment Corporation Energy Tech.Research Institute,Nanchang Jiangxi,330000;SPIC JiangXi Electric Power CO.,LTD.FenYi Power Plant,Xinyu Jiangxi,336607)
出处
《电子测试》
2021年第24期44-46,共3页
Electronic Test
关键词
朴素贝叶斯算法
智能电厂
监控
夜间视频
人脸识别方法
Naive Bayes algorithm
Intelligent power plant
monitor
Night video
Face recognition method
