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Research on Moving Objects Detection Algorithm in Intelligent Vision Monitor System

Author: ZhouJie
Tutor: ZhangBaoFeng；ZhuJunChao
School: Tianjin University of Technology
Course: Detection Technology and Automation
Keywords: Target tracking Three frame difference SIFT image match Camshift Kalman
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 85
Quote: 3
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Abstract


The intelligent vision monitoring is an extremely important research area on computer intellectualization. It has been applied in numerous domains such as the safe monitoring, the intelligent transportation, the military guidance, the visual guidance, the weather analysis as well as the medical diagnosis. In addition, the union of the monitoring system and the wireless network has expanded monitoring system’s application situation. Therefore strengthening the intellectualization, network and wireless research to monitoring system has the enormous academic value, social value and economic value. In vision monitoring, how carries on the track and classification to the moving goal in the scene is the universal concerned matter for the people, which is also a hot topic at present, specially under complex background outdoor, because the situations such as image scale and rotation change, illumination change, translation, deformation and so on often exist, it is difficult to track and recognize goal accurately.This article seeks effective solution after the research on many kinds of commonly used tracking and matching algorithms, achieves the highly accurate, high robust, the high timely moving target tracking and matching algorithm. The article takes human or vehicle as examined object, in the situation of camera being fixed, under the complex background, exams and tracks moving goal in the vision monitoring system, and carries on classification to the moving goal, then achieves intellectualized goal.The main research content is as follows:1. Studied the image pretreatment algorithm including the image intensification, the image smoothing, the image sharpening and so on, and carried on the analysis to them, drawed the conclusion.2. Studied the frame difference algorithm, the background subtracted method and the optical low algorithm, analyzed the good and bad aspects.Proposed“the united algorithm of three frame difference and background subtracted algorithm”. This algorithm eliminates“double image”and“empty phenomenon”coming from the frame difference algorithm, can extract the moving goal completely. The experimental result indicated that this algorithm can adapt environmental variations effectively, achieve the goal of examining moving object accurately and fast.3. Studied the image registration method and the image matching technique. Proposed“the SIFT matching algorithm”, and unites three frame difference and background subtracted algorithm to distinguish the human or vehicle. The experimental result indicated that the SIFT algorithm can match robustly and accurately to target with same template under the situation of image scale and rotation change, illumination change, translation, deformation and so on. Uniting three frame difference and background subtracted algorithm can match fast and accurately to objects with different template and classify them under the situation above.4. Studied Camshift and Kalman algorithm.Proposed“the united algorithm of Camshift and Kalman”. This algorithm is uniting hue histogram and the filter forecast in the Kalman filter frame to solve the moving goal’s scale change and deformation. The experimental result indicated that this united algorithm can track moving target accurately and the outline mark’s size maintains invariable basically when the color difference between background and object is great.

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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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