摘要
受有效传输速率的限制,远程图像监控系统的清晰度一般较低,为提供较为清晰的画面,必须在前端进行运动检测,以便在出现异常情况时实施抓拍;本文给出了一种在监控前端对图像进行运动检测和分析的监控系统,采用了Kalman滤波动态背景生成、信息熵最大化的运动判决门限等算法的原理,并采用嵌入式系统加以实现;当符合规则的运动出现在连续传输的画面中时,它可以抓拍异常情况的高清晰度图片并传回监控中心,从而有效解决了清晰度和传输速率间的矛盾;系统运行结果表明,对于自然光线变化的场合,该方法具有检出率高、虚警率低的特点.
Because of the limitation of transmission channel,the image articulation of remote surveillance system is generally low. In order to get high articulation image while exceptional event occurs, it must go on with motion detection in the front of surveillance system. This article gives a surveillance system before which can go on with motion detection and analyze its result. This system adopts principle of Kalman filter to get dynamic background and arithmetic of getting maximum entropy threshold in motion detecting, and implements it by embedded system. This system can captures high articulation image and transmit it back to monitor center when motion presetted appears in serial transmitting images, then it effectively avoids contradiction between image articulation and transmitting speed. Results from the working system show that the method holds features of high detected probability and low constant false alarm rate(CFAR) in the environment of changing nature beam.
出处
《西安工业学院学报》
2006年第2期131-135,共5页
Journal of Xi'an Institute of Technology