基于OpenCV的视频监控与跟踪系统研究

Research on Video Surveillance and Tracking System Based on OpenCV

论文对当前视频监控系统智能化、自动化需求进行调研分析,基于OpenCV计算机视觉库、Visual Studio 2017和MFC框架设计并实现智能化视频监控与跟踪系统。系统主要对视频监控相关的图像处理方法与机器视觉算法进行研究并提供智能化监控跟踪解决方案,系统研究重点阐述了视频数据预处理中的图像灰度化和图像滤波操作,并在此基础上通过高斯混合背景差分提取运动目标,进行阈值二值处理实现与背景分离,目标完成检测后,采用Camshift进行目标跟踪并结合卡尔曼滤波完成目标运动预判报警功能。实验结果表明,系统能有效检测运动目标完成报警功能。

This paper investigates and analyzes the current intelligence and automation requirements of video surveillance system,designs and implements intelligent video surveillance and tracking system based on OpenCV computer vision library,Visual Studio 2017 and MFC framework.The system mainly researches image processing methods and machine vision algorithms related to video surveillance and provides intelligent solutions of monitoring and tracking.The system research focuses on image gray processing and image filter operations in video data preprocessing.On this basis,Gauss mixture background-difference method is used to extract moving targets,and image binarization is used to achieve background separation.After the target is detected,the target tracking is performed by using Camshift and combined with Kalman filter to achieve the target motion prediction and alarm function.The experimental results show that the system can effectively detect the moving target to achieve the alarm function.