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Research on Vehicle Detection Method of Intelligent Transportation System

Author: MaZongShun
Tutor: QinBo
School: Ocean University of China
Course: Computer Software and Theory
Keywords: Background update Real-time detection Shadow recognition Feature recognition
CLC: U495
Type: Master's thesis
Year: 2008
Downloads: 84
Quote: 0
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Abstract


Urban transport is one of the city's critical infrastructure is necessary for urban economic development and people's lives for a cause. Not only does it meet the travel needs of urban residents, in a sense its normal functioning of the city played an important role. In recent years, with the economic development, traffic demand increasing urban traffic congestion, frequent traffic accidents and traffic deterioration of the environment have become a common problem facing the world today. The traffic problem is a complex problem, from the point of view of road or vehicle alone to consider, it will be difficult to solve the traffic problems. In this context, the combined vehicle and background system to solve the traffic problems thought to remember with affection, and vehicle detection technology is one of important technologies of this idea. The real-time detection and location of the moving vehicle is an important part of the intelligent transportation system. So far, many scholars have been conducting research in related fields. But it also faces many problems, such as the target shadow, real-world scene of the shooting noise, light and weather conditions change, will affect the accuracy of the target detection. In recent years, domestic and foreign scholars have conducted extensive research based on video image of the moving target detection. Conventional vehicle detection methods: background subtraction method, the time difference method, optical flow method. These methods, the background subtraction method due to its relatively small amount of computation, and can be added to background update technology background adaptive updates can be more accurate segmentation of moving objects, which is widely used in moving target detection and segmentation, because of its own shortcomings, the majority of scientists according to the different needs of its improvement. The time difference method in a continuous sequence of images in two or three adjacent interframe pixels based on the time difference, but it can not be completely extracted all of the relevant characteristics of the pixels in the moving entity internal prone to cavitation. And its application has been limited due to the fairly large amount of calculation, the anti-noise performance differential motion detection method based on the optical flow, dependent on the particular hardware device. Vehicle detection method proposed in this paper, the adaptive background updating method based on the moving region applied to the video image moving target detection segmentation techniques, which can quickly and accurately segmented moving target and then identify the shaded portion of the vehicle and the wheel part. The test results proved that this method can be greatly improved vehicle detection accuracy and quality, to achieve our expectations, with good usability.

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CLC: > Transportation > Road transport > Technical management of traffic engineering and road transport > Computer applications in road transport and highway projects
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