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A motion detection-based framework for improving image quality of CCTV security systems.

机译:基于运动检测的框架,用于提高CCTV安全系统的图像质量。

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摘要

Closed-circuit television (CCTV) security systems have been widely used in banks, convenience stores, and other facilities. They are useful to deter crime and depict criminal activity. However, CCTV cameras that provide an overview of a monitored region can be useful for criminal investigation but sometimes can also be used for object identification (e.g., vehicle numbers, persons, etc.). In this paper, we propose a framework for improving the image quality of CCTV security systems. This framework is based upon motion detection technology. There are two cameras in the framework: one camera (camera A) is fixed focus with a zoom lens for moving-object detection, and the other one (camera B) is variable focus with an auto-zoom lens to capture higher resolution images of the objects of interest. When camera A detects a moving object in the monitored area, camera B, driven by an auto-zoom focus control algorithm, will take a higher resolution image of the object of interest. Experimental results show that the proposed framework can improve the likelihood that images obtained from stationary unattended CCTV cameras are sufficient to enable law enforcement officials to identify suspects and other objects of interest.
机译:闭路电视(CCTV)安全系统已广泛用于银行,便利店和其他设施。它们对于阻止犯罪和描述犯罪活动很有用。但是,提供受监视区域概述的闭路电视摄像机可用于刑事调查,但有时也可用于物体识别(例如,车辆号,人员等)。在本文中,我们提出了一个改善CCTV安全系统图像质量的框架。该框架基于运动检测技术。框架中有两台相机:一台相机(相机A)是使用变焦镜头进行移动物体检测的固定焦点,另一台相机(相机B)是使用自动变焦镜头来捕捉更高分辨率图像的可变焦点。感兴趣的对象。当相机A在监视区域中检测到运动物体时,由自动缩放焦点控制算法驱动的相机B将拍摄感兴趣物体的高分辨率图像。实验结果表明,提出的框架可以提高从固定式无人监控摄像机获得的图像足以使执法人员识别嫌疑人和其他感兴趣物体的可能性。

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