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Moving Object Recognition Video Monitoring System Design and Implementation

Author: ZhangQiang
Tutor: YuanWei
School: Huazhong University of Science and Technology
Course: Communication and Information System
Keywords: Video Surveillance Image Processing Moving Object Recognition OpenCV
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 125
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Abstract


With the extensive application of video surveillance systems, video surveillance technology more and more attention. Moving Object Recognition as a video surveillance system image sequence processing is a basic requirement, has become a research hotspot. It is the object of processing from the video capture device to obtain a continuous image sequence, the purpose is to detect and extract the image of the moving target, and thus to obtain the description of the moving target and pattern matching to obtain the objective attributes, and thus determine the target behavior, movement, and other information. Moving target identification to achieve the general steps are: video decoding, image sequences smoothing, moving target detection and identification, and eliminate false positives. Image sequences by Gaussian smoothing or median filtering methods such as image sequences denoising process. Moving target detection and identification of commonly used algorithms are background subtraction, inter-frame difference method and the optical flow method. The practical application of video sequences under the shadow will appear, background disturbance, target occlusion and other issues, the role of eliminating false positives is to use an appropriate algorithm to eliminate these negative effects. This article focuses on the video surveillance system moving target identification process design and implementation. Video surveillance systems capture devices typically use fixed cameras, this constraint condition in which a moving target recognition algorithm design and implement them. In accordance with the general procedure for moving target identification, first introduced the video image sequence filtering algorithm Gaussian smoothing and median filtering algorithm; then compared the background subtraction, inter-frame difference method and the optical flow method which three traditional moving target recognition algorithm, and based on background subtraction method proposed for fixed cameras median background subtraction as the realization of the system; followed by goals against noise and false negatives analyzed aggregated and made a threshold method and the expansion area of ​​law as a corresponding solution ; and then gives the system the key algorithm is based on OpenCV (Open Computer Vision, open computer vision software platform) implementation process and detailed test results. After laboratory tests proved that the design of this moving target identification video surveillance system can effectively remove the noise, the correct detection and identification of moving targets, reducing the false positive rate, the video surveillance system design moving target identification with a certain reference value.

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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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