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Method and Key Technique Research about Vision-based Traffic Flow Detection

Author: LiHui
Tutor: XingJianPing
School: Shandong University
Course: Communication and Information System
Keywords: Video detection Vehicle Identification Background subtraction Shadow Detection Intelligent Transportation
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 148
Quote: 1
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Abstract


The strong development of the national economy in a positive impact to the progress of mankind and life , but also a huge negative impact to road traffic . In this context , the Intelligent Transportation Systems (ITS) combine the vehicle and the road pointed out the direction of development for modern traffic management . Where traffic flow parameters is a vital part of the ITS . Favor of low price and high flexibility more and more countries in the world for its ease of installation , video - based traffic flow detection . Based on the video traffic detection ultimate goal is the identification and detection of the vehicle . This article by comparison of several detection methods using the combination of frame difference background subtraction method to be detected on the vehicle . The method of generating in the background using the Gaussian mixture modeling approach . Taking into account the negative impact of the the vehicle shadow of vehicle detection , this paper focuses on the shadow removal method . Taking into account the computational complexity and accuracy of detection , this paper presents a CIELuv space background modeling and combination of texture information detection detect shadows . The tests showed that the improved method proposed in this paper can accurately extract the vehicle shadow , and the target vehicle information intact . The vehicle identification is carried out in the basis of successful background difference moving foreground . First image segmentation processing for the foreground image , the identification of the vehicle and then through the target area and contours of the feature extraction . Count and velocity analysis of the movement of vehicles identified , thereby obtaining the status of the current traffic data. Verified by experiments, based on the detection of the combination of frame difference background subtraction of traffic flow , it is possible to accurately detect the vehicle prospects . CIE Luv space L component can be accurately and quickly carry out the modeling of the background and the detection of the shadow , and performed a valid improvement on existing methods . The video detection method computational complexity , high detection accuracy and real-time traffic parameters such as traffic flow , speed , intelligent traffic can become an important means of detection .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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