Visual Surveillance Using Absolute Difference Motion Detection System

Abstract : Surveillance is the monitoring of the behavior, activities, or other changing information, usually of people for the purpose of influencing, managing, directing, or protecting them. As security is becoming the primary concern of society and hence having a security system is becoming a big requirement. Video surveillance plays a vital role in security systems. This paper describes the ability to recognise objects and humans, to describe their actions and interactions from information acquired by sensors using absolute difference motion detection technique. Real-time implementation is achieved by using a Global System for Mobile Communication (GSM) modem for SMS (Short Message Service) notification. The ablity of tracking and recognition of the visual device was implemented using OpenCVTM for displaying an output. The detected objects motion is being captured and stored in HDD.
 EXISTING SYSTEM :
 ? A large literature exists concerning moving object detection in video streams and to construct reliable background from incoming video frames. ? Because of the different placing of the cameras, its not possible to use space-time constraints among the exists and entrance area of the camera. ? The length of this paper is restricted, we review here only recent researches on the major existing methods for gait recognition. ? Surveillance using multiple different sensors seems to be a very interesting subject. ? The main problem is how to make use of their respective merits and fuse information from such kinds of sensors.
 DISADVANTAGE :
 ? Security is becoming the primary concern of real life due to increasing population and scarcity of jobs and growing problems especially in urban cities, the number of antisocial activities, etc. ? Motion Detection & tracking is the basic problem that arises in various computer vision applications. ? We have proposed two methods to overcome the problem of object tracking in varying illumination condition and background clutter. ? In multiple camera object tracking, the problem of correspondence occurs and the job is to identify if the object is being tracked in some camera or the new object entered the camera FOVs. ? Visual surveillance using multicamera brings problem such as camera calibration, automated camera switching and data fusion.
 PROPOSED SYSTEM :
 • We have proposed two methods to overcome the problem of object tracking in varying illumination condition and background clutter. • A robust object tracking algorithm is proposed to overcome the problem of illumination variation. • It is proposed to detect and track a moving object using frame differencing. • In the proposed algorithm dilation and erosion is used iteratively till the foreground object is completely segmented from the background. • The primary purpose of this paper is to give a general review on the overall process of a visual surveillance system.
 ADVANTAGE :
 ? In motion detection, a study on different recent background subtraction available in the literature have been studied and their performance tests on the different video test sequence. ? It should be noted that robust motion detection is a critical task and its performance is affected by the presence of varying illumination, background motion, camouflage, shadow, and etc. ? It is a key technology to fight against terrorism, crime, public safety and for efficient management of traffic. ? The work involves designing of efficient visual surveillance system in complex environments. ? Sometimes object tracking involves tracking of a single interested object and that is done using normalized correlation coefficient and updating the template.

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