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