DocumentCode
1773443
Title
Wireless webcam based car burglar detection system
Author
Wai Kit Wong ; Kim Teng Leow
Author_Institution
Fac. of Eng. & Technol., Multimedia Univ., Bukit Beruang, Malaysia
fYear
2014
fDate
3-5 June 2014
Firstpage
1
Lastpage
4
Abstract
This paper presents a wireless webcam based smart visual surveillance system with real-time moving object detection, classification and tracking capabilities for car burglar detection. This image processing based car detection system can handle object detection, classification and tracking in both indoor and outdoor environments. The classification algorithm makes use of the temporal tracking results and the shape of the detected objects to accurately classify objects into classes such as human, human group and vehicle. The purpose of designing a smart surveillance system that is based on the integration of motion detection and visual tracking is to achieve a better performance in helping the security officers to prevent car burglar crimes from escalating. Experimental results show that the proposed car burglar detection algorithm is able to achieve accuracy as high as 96.2% in optimum setting with routine time of 1.28 seconds.
Keywords
cameras; image classification; image motion analysis; object detection; object tracking; surveillance; traffic engineering computing; image processing based car detection system; indoor environments; motion detection integration; object classification algorithm; object tracking capability; outdoor environments; real-time moving object detection; visual tracking; wireless Webcam based car burglar detection system; wireless Webcam based smart visual surveillance system; Accuracy; Communication system security; Real-time systems; Security; Surveillance; Webcams; Wireless communication; Image Processing; car burglar detection algorithm; surveillance system; webcam imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent and Advanced Systems (ICIAS), 2014 5th International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4799-4654-9
Type
conf
DOI
10.1109/ICIAS.2014.6869466
Filename
6869466
Link To Document