基于Adaboost算法的油田值守站场进入人员身份自动化识别系统  

Adaboost Algorithm Based on the Oil Field Guard Station Entry Identity Automatic Identification System

作　　者：白宪丽 BAI Xianli(Science and Technology Information Department,CNPC Liaohe Oil Field Company,Panjin 124010,China)

机构地区：[1]中国石油辽河油田分公司科技信息部,盘锦124010

出　　处：《自动化与仪表》2025年第4期91-94,共4页Automation & Instrumentation

摘　　要：油田值守站场环境复杂嘈杂,导致对进入站场的人员身份识别存在困难。Adaboost算法具有较强的适应性,适用于复杂环境。为此,研究了基于Adaboost算法的油田值守站场进入人员身份自动化识别系统。该系统通过视频监控模块实时采集人员视频图像,以Adaboost算法为核心的人脸检测模块检测人脸区域,再以SIFT算法为核心的身份识别模块提取人脸特征并与员工信息库比对,实现身份自动化识别。结果显示,该系统人脸检测、特征提取效果显著,能应对不同光照条件,精准识别人员身份,并在识别不通过时预警,有效避免油田风险事件。The complex and noisy environment of oilfield duty stations makes it difficult to identify the personnel entering the battlefield.The Adaboost algorithm has strong adaptability and is suitable for complex environments.Therefore,an automated identification system for personnel entering oilfield duty stations based on Adaboost algorithm was studied.The system collects real-time personnel video images through a video surveillance module,detects facial regions with a face detection module based on Adaboost algorithm,and extracts facial features with an identity recognition module based on SIFT algorithm and compares them with an employee information database to achieve automated identity recognition.The results show that the system has significant effects on face detection and feature extraction,can cope with different lighting conditions,accurately identify personnel identities,and issue warnings when recognition fails,effectively avoiding oilfield risk events.

关 键 词：ADABOOST算法 油田值守站场 进入人员 身份识别 人脸检测 SIFT算法 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]