Vehicle speed detection using frame differencing for smart surveillance system

Rahim, Hasliza A.; Sheikh, Usman Ullah; Ahmad, Robiah; Zain, Aini Syuhada Md; Ariffin, W. N. F. W.

doi:10.1109/isspa.2010.5605422

Cited by 12 publications

(21 citation statements)

References 6 publications

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“…Using CCTV, it is also possible to register state license plates [11] and calculate the vehicle speed using the total distance travelled and the time taken from start to finish of selected section. CCTV technology is not affected by vehicle changing lanes, because the cameras monitor all lanes and are interconnected [12], [13].…”

Section: A State-of-the-art Sensorsmentioning

confidence: 99%

PDMS-FBG-Based Fiber Optic System for Traffic Monitoring in Urban Areas

et al. 2020

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This article introduces fiber Bragg grating (FBG) system for monitoring selected traffic flow parameters in urban areas. The system is able to monitor traffic density or speed of cars driving in single lane. The proposed system consists of five Bragg gratings encapsulated in Polydimethylsiloxane polymer and is characterized by easy and inexpensive installation in the milled upper layer of the road covered with an asphalt mixture. The results of first operational tests presented in this study include 3978 passing vehicles of various specifications. The system's vehicle detection success rate is 99.62%. And further, a mean absolute error 1.35 kph and a relative error 2.62% when measuring vehicle speed.

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Section: A State-of-the-art Sensorsmentioning

confidence: 99%

PDMS-FBG-Based Fiber Optic System for Traffic Monitoring in Urban Areas

et al. 2020

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“…They also replaced the widely used morphology operations by adopting a spatial filter to suppress various noises due to the swaying of the tree branches. Reference [9] detected the moving vehicles using temporal differencing method, also known as frame differencing method. Reference [12] proposed the framework that detects the changes in the video scenes from optical flow and encodes using hidden Markov model to classify abnormal events.…”

Section: Related Workmentioning

confidence: 99%

Smart Objects Identification System for Robotic Surveillance

Shafie

Ibrahim

Rashid

2014

Int. J. Autom. Comput.

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Video surveillance is an active research topic in computer vision. In this paper, humans and cars identification technique suitable for real time video surveillance systems is presented. The technique we proposed includes background subtraction, foreground segmentation, shadow removal, feature extraction and classification. The feature extraction of the extracted foreground objects is done via a new set of affine moment invariants based on statistics method and these were used to identify human or car. When the partial occlusion occurs, although features of full body cannot be extracted, our proposed technique extracts the features of head shoulder. Our proposed technique can identify human by extracting the human head-shoulder up to 60%-70% occlusion. Thus, it has a better classification to solve the issue of the loss of property arising from human occluded easily in practical applications. The whole system works at approximately 16−29 fps and thus it is suitable for real-time applications. The accuracy for our proposed technique in identifying human is very good, which is 98.33%, while for cars identification, the accuracy is also good, which is 94.41%. The overall accuracy for our proposed technique in identifying human and car is at 98.04%. The experiment results show that this method is effective and has strong robustness.

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“…The number of vehicles on the roads is continually increasing with the growth of the world population. The number of accidents also increasing due to limited capacity of the infrastructure to handle the increasing number of vehicles [1][2][3][4][5][6][7]. One of the prominent reasons of the road accidents is the over speeding.…”

Section: Introductionmentioning

confidence: 99%

Design of Electronic System for Speed Detection of Vehicles

Hindi¹

2020

IJATCSE

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This paper proposes a novel vehicle speed identification electronic system, which is cost effective and simple. The number of vehicles on the roads is increasing day by day and it is vital to detect the speed of the vehicle to avoid the accidents. There are several methods reported in past for the speed detection using laser gun. However, those methods are costly and use complex algorithms. The countries with developed economies can afford the expensive technology however, the countries with the struggling economies still rely on the manual and semi-automated methods of vehicle speed detection. The proposed method is based on the images processing of the vehicle plate number, which are captured using camera. The experiments were performed to evaluate and validate the reliability of the proposed method. The results show that the proposed electronic system offers efficient in detecting the speed of vehicles at lower cost.

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Vehicle speed detection using frame differencing for smart surveillance system

Cited by 12 publications

References 6 publications

PDMS-FBG-Based Fiber Optic System for Traffic Monitoring in Urban Areas

PDMS-FBG-Based Fiber Optic System for Traffic Monitoring in Urban Areas

Smart Objects Identification System for Robotic Surveillance

Design of Electronic System for Speed Detection of Vehicles

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