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Dynamic Image Analysis Research Based on Biological Vision Principle

Author: ZhaoHao
Tutor: WangZhengZhi
School: National University of Defense Science and Technology
Course: Control Science and Engineering
Keywords: Dynamic image Image sequence Biological vision Motion perception Direction detection Feature tracking signals
CLC: TP391.41
Type: Master's thesis
Year: 2007
Downloads: 187
Quote: 4
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Abstract


Dynamic image analysis is a very active area of ??research. Traditional machine vision theory has encountered some difficulties in dealing with sports issues. Starting from a different angle, through in-depth study of biological vision theory, based on recent research results at home and abroad, gives a real image sequences can be used for motion perception neurodynamics model and its simulation and analysis. Currently known perception of movement and the direction of motion relates to the visual cortex of V1, V2,, V3,, the MT and MST area, in which V1-V2 is a static image processing passage, MT-MST is moving image processing passage. Grossberg outline of the shape of the moving boundary system (Formotion BCS) is built on the basis of these studies, a more successful motion perception model. However, it focuses on the visual analysis of the psychological phenomenon, can not be directly used for motion detection in the real scene. This article studies the special requirements of the basic characteristics of motion perception and real scene dynamic image processing, and integrated several motion model to establish a new mechanism of dynamic image processing in a parallel real scene. First, improving the static boundary contour system (SBCS) luminance equalization pretreatment conditions of different input image, and calculate the static image boundary; Secondly, the design of the target background separation mechanism for the extraction of moving targets, not only simplifies the processing scene can give a good solution to the occlusion problem; Finally, the perception of the movement direction of the core calculation model. The idea is: first by transient cell movement direction detection, but due to the presence of the aperture problem the directionality goal here is fuzzy; then through short-range filter network and space competition network, feature tracking signal extraction; MT-MST in the feedback loop, the feedback characteristics of the group based on the long-range direction and front Note diffusion mechanism to achieve a tracking signal caused by the characteristic motion capture perceived overall consistency in the direction of the moving target. Further, a static path and a dynamic path mutual feedback to further enhance the strength of the dominant signal. Paper also based on the model of the computer simulation. From the geometry of the the structured scene to the real scene of natural images, more comprehensive selection and analysis of the various types of dynamic image sequences. From the simulation results, the model calculation accuracy, adaptability explains, to some extent, the model is consistent with the biological visual motion processing mechanism. Finally, this research work are summarized biological motion vision and future prospects.

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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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