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Research on the Key Technologies of Intelligent Transportation Video Surveillance System

Author: ChenJingZhu
Tutor: SongXueZuo
School: Jiangsu University
Course: Communication and Information System
Keywords: Intelligent Video Surveillance Moving target detection Target tracking Gaussian mixture model Support Vector Machine
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 283
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Intelligent video surveillance is an emerging field of computer vision research directions and topics at the forefront of concern, without human intervention, automatically analyzes the image sequence to achieve the dynamic scene moving target detection, tracking and behavior understand the operation and results of the analysis to determine whether an alarm. Intelligent video surveillance system to overcome the defects of the traditional monitoring needs of real-time observation, saving manpower and resources, enhanced monitoring to determine the accuracy in the monitoring of the military, transportation, banking and other important places, it has a broad application prospects. In this paper, the camera is stationary outdoor traffic intelligent monitoring application background, moving target detection, tracking and classification on the basis of analysis of the existing results, improve and achieve. On this basis, completed the design and development of intelligent video analysis system. The main contents are as follows: 1. Moving target detection: first comparative analysis of several commonly used moving target detection method, select Gaussian mixture model-based background subtraction. Traditional Gaussian mixture model of light sensitive, prone to ghost defects, this paper presents an improved mixture Gaussian background model algorithm. Simplify the background model to build and initialization process, the establishment of S and V component mixture model, reducing the computational complexity of the system; followed by the introduction of the background update process to update factor to change the background area for redevelopment, to solve the problems of background mutation; Finally, The HSV color model to detect and remove the shaded area in the foreground, and the use of morphological filtering method to remove background noise to improve the practicality and accuracy of the moving target detection system. 2 Moving Target Tracking: This article selected Mean Shift algorithm to accomplish the task of target tracking system, the Mean Shift algorithm tracking Kalman filtering prediction Mean Shift algorithm combining the fast-moving target tracking result is not satisfactory, algorithm to achieve improvements to the original algorithm. Experiments show improved target tracking algorithm can obtain higher tracking stability. 3 moving target classification: first discuss several commonly used classification method, select the method of support vector machine to classify the moving target. For intelligent video surveillance function of the traffic scene is very much, the main achievement of the moving target detection, virtual cordon alarm, the virtual warning zone alarm and license plate recognition and other functions. The test results demonstrate the effectiveness of this article moving target detection, tracking and classification algorithm, monitoring can achieve the desired effect, and can be used in the conditions of the actual scene moving target detection, tracking, classification and alarm functions.

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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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