motion detection and theft control system

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MOTION DETECTION AND THEFT CONTROL SYSTEM

Abstract:

In todays competitive environment, the security concerns have grown tremendously.In the modern world, possession is known to be 9/10ths of the law. Hence, it isimperative for one to be able to safeguard ones property from worldly harms such as thefts, destruction of property, people with malicious intent etc.

Due to the advent of technology in the modern world, the methodologies usedby thieves and robbers for stealing have been improving exponentially. Therefore, it isnecessary for the surveillance techniques to also improve with the changing world.With the improvement in mass media and various forms of communication, it is nowpossible to monitor and control the environment to the advantage of the owners of theproperty. The latest technologies used in the fight against thefts and destruction are thevideo surveillance and monitoring. By using the technologies, it is possible to monitorand capture every inch and second of the area in interest.

However, so far the technologies used are passive in nature, i.e., the monitoring systemsonly help in detecting the crime but do not actively participate in stopping or curbingthe crime while it takes place. Therefore, we have developed a methodology to detectthe motion in a video stream environment and this is an idea to ensure that themonitoring systems not only actively participate in stopping the crime, but do so whilethe crime is taking place.

Hence, a system is used to detect any motion in a live streaming video and oncemotion has been detected in the live stream, the software will activate a warning systemand capture the live streaming video.


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INTRODUCTION:

Video surveillance and security systems have become very common in modem days. Thiskind of system can easily be found in places like retail stores, banks, supermarkets, airports,commercial buildings and even private premises. There are two kinds of video surveillance and

security systems: analogue system and digital system. In traditional systems for securityoperations, cameras are used to deliver analogue video images to monitors or time-lapsevideocassette recorder (VCR). Although many local image processing functions are possible toimprove the system application, this requires a lot of processing resources and high-power-consuming hardware. Although digital video surveillance and security system is widely used,analogue system still serves as a cheaper alternative. Charge coupled devices (CCD) camera anddigital camera one among the most popular cameras used in the system.

Motion detection is the ability to recognize the presence of movements. There are many differentways to detect motion. The conventional way is by using either active sensor or passive sensor.

The new method to detect motion is "vision motion detection". It is the artificial way of machinevision system compared to human's vision in detecting motion. Motion detection is the mostimportant feature in digital video surveillance system. It gives the camera the capability tocapture when needed rather than capture all the time and this leads to huge reduction in storagespace . Al arm can also be tr iggered when unexpected motion i s detected. Th is reli eves the personnel i n moni torin g at all time.

So my idea was to take a picture from a web cam every period of time (make it the current picture) and compare it with a previous picture and if we find a big difference between them wewill save both pictures else will free memory from the old picture and make the new picture thecurrent picture.


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First, grab image from web cam called Old. Second, grab another image fromweb cam after a while, called Current. Compare Current& Old by comparing each pixelcolor. If difference is greater than tested value (according to the quality of your web cam& light system you are using is 60 or 50 Hz), then save the two pictures. Finally, makethe old picture the Cur picture. Back to second step (infinite loop).

Three key factors brought on the popular use of the digital video recorder. They are

The advancement in compression capability, allowing more information to be storedon a hard drive. (Roundthe- clock surveillance produces a lot of information.)

The cost of a hard drive, which has dropped dramatically in recent years.

The storage capacity of a hard drive, which has increased dramatically in recent years.

Objective

The main objectives of this thesis project are as stated in the following:


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I. To investigate if motion detection is possible for web camera.

II. To develop a low cost security system using web camera.

1Il. To develop software with motion detection f unction algorithm.

This project aims to achieve web camera application system with automatic motiondetection capability. The main idea is to develop a low cost surveillance system usingweb camera, which runs the software that is incorporated with motion detectionalgorithm. It uses the concept of "motion detection by vision" to achieve motiondetection capability where no hardware sensors are required.

The automatic motion detection capability helps to reduce archive space andmonitoring manpower. The system would be a simple "do-it-yourself' system, which

means anyone can just setup by himself/herself.

In this project web camera is chosen as it is low cost captured to other capture devices.It is used as video capture device for the motion detection in surveillance purpose. Onlya web camera and a PC required for this purpose and therefore it is cheap instead ofsophisticated surveillance system that involves Charge Coupled Devices (CCD) cameraor digital camera.


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Exciting system

Digital surveillance systems are mostly specifically designed for commercial use and ithas always been out of reach for other users. The cost for CCD cameras, networking devices andthe software designed for this system has made it inaccessible and unpractical for home users

with moderate requirements. Also, not all the existing product has the motion detection function.

In traditional systems for security operations, cameras are used to deliver analogue videoimages to monitors or time-lapse videocassette recorder (VCR). Although many local image

processing functions are possible to improve the system application, this requires a lot of processing resources and high-power-consuming hardware. Although digital video surveillanceand security system is widely used, analogue system still serves as a cheaper alternative.

Proposed System

Most of the video surveillance and security systems in the market do notIssue alarms in real time, manual monitoring system are costly in term of manpower. This can beovercome by a real time motion detection system with the ability to automatically analyze thevideo images and archive the images with moving objects.

The flaws of existing surveillance and security system would be overcome by a real time motiondetection system with the ability to automatically analyze the video images and archive theimages with moving objects and it alerts automatically when the motion detects from the view of camera. Therefore, a digital surveillance system based on web camera and targeted for small-

scale user is developed.

.So our Proposed Project gives the camera the capability to capture when needed ratherthan capture all the time and this leads to huge reduction in storage space .


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Modules description:

This thesis project consists of three main stages, namely hardware setup, simulation and

implementation. Hardware setup and capturing Simulation and Comparing frames Implementation and Alert generation system

Hardware setup:

The first stage is setting up the system of which consists of PC and web camera. The webcamera is only operable with the web camera driver installed in the PC.Our Project recognize theinstalled Hardware (WEB CAM ) , It provides control for the setting facilities of camera such as

Resolution, size of the frame in pixels, and Rate of frame to be captured.System capture the view at particular rate of speed as specified at the settings of camera.Captured image is stored temporarily.

Simulation and Comparing frames

In the second stage, simulation done on the frame images using VB .Net with ImageProcessing Module as simulation tool to investigate the possibilities of motion detectionalgorithm on images captured by web camera.

In this stage First, grab image from web cam called Old. Second, grab another imagefrom web cam after a while, called Current. Compare Current& Old by comparing each pixel

color. If difference is greater than tested value (according to the quality of your web cam & lightsystem you are using is 60 or 50 Hz), then save the two pictures. Finally, make the old picturethe Cur picture. Back to second step (infinite loop).

Implementation and Alert generation system

In the third stage, implementation process is done by coding the motion detectionsoftware using Microsoft Dot Net. The algorithm that was successfully simulated is used as thereference for forming the working mechanism in creating motion detection software.

In this stage the new frames will be stored at specified Locations, and alert system will begenerated with any sound alert Or GSM based message alert for anybody.


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Algorithm:

The motion detection method that was selected is a background subtraction technique. A previous frame is used as the background, and its color is subtracted from the current frame todetect any differences in the new frame. This background frame will be resettable at any time by

the user, but the first background frame used is the first frame that is processed by thea pplication. A sliding window for the background frame was considered as well. The slidi ngtime window would change the background frame at intervals so that it would come closer towhat we are seeing in the current frames. This would improve the motion detection overall, but itwould also eliminate any detected blobs that stop moving. Once the blob stops moving, the

background sliding window would slowly incorporate the blobs into the background.


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Forms


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System Testing

The system was tested using ad hoc tests. I focused on the areas of the system that weremost important, as well as spending time testing areas of concern. For all the tests, the camerawas set three and six feet above a surface. The camera used for testing was the Logitech 3000webcam. The webcam has a resolution of 640 x 480. First the motion detection was tested byvarying the threshold level between .3, .5, and .7 against different colored backgrounds.

To test the motion tracking functionality, I used my hands as well as a laser pointer toensure the system was following and naming the blobs properly.

CONCLUSION

A video monitoring & detection system was thus developed successfully in this paper.This system mainly provides an efficient method for surveillance purposes and is aimed to be


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highly beneficial for any person or organization. Thus, a motion based change detection in avivideo format was completed and successfully implemented. The future scope of the work donecould be as follows: the due course of time as we started to understand the minute details of our work, we significantly realized that our software would be tremendously important in the futureworld. Following changes or additions can be done on our work to include some new features.

With the existing alarm system, advancement can be included and SMS can be sent to the user when motion is detected.

The stored video can be automatically transferred to some email account so that an extra backup data can be used.

A user_id and password can be given to a user so that unauthorized people dont haveaccess to the software.

A facility for the user can be given where he can mainly monitor only a small specificarea in the range of the web cam.

In the futu re, the user can be provided a remote access to this software from someremote PC through internet.

Include an option to take snaps periodically, manually or automatically.

Work could be done to make the system more users friendly for a layman user

Bibliography


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Bradski, G.R., & Kaehler, A. (2008) Learning OpenCV: Computer Vision with the OpenCV

Library. ORielly. Davies, E.R. (2005) Machine Vision: Theory, Algorithms, Practicalities. MorganKaufmann.TUIO Community (2009), http://www.tuio.org/ Pompeu Fabra University.

Reactable (2009), http://www.reactable.com/ Pompeu Fabra University.OpenCV Wiki (2009), http://opencv.willowgarage.com/wiki/Processing 1.0 (2009), http://processing.org/ Ben Fry and Casey RaesBlob Detection (2009), http://www.v3ga.net/processing/BlobDetection/ v3ga.

oscP5 (2009), http://www.sojamo.de/libraries/oscP5/ Andreas Schlegel.

motion detection and theft control system

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