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Traffic Flow Amount Detection Technique Research Based on Morphology

Author: ZhangKeWei
Tutor: GuoYuanShu
School: Chang'an University
Course: Applied Computer Technology
Keywords: Traffic flow Video detection Mathematical Morphology Lane dynamically set Cross - lane And lane
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 46
Quote: 1
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Abstract


The traffic flow is the important parameters of the intelligent transportation system , real-time , reliable traffic flow information is an important basis to determine traffic conditions . Video traffic flow detection techniques than traditional detection technologies has abundant information , set up a flexible , low-cost and many other advantages , has become a research focus at home and abroad . According to the actual traffic conditions , combined with live traffic flow characteristics of the video , to video-based traffic flow detection technology processes for a more detailed study of the sequence of traffic flow detection technology , especially on the basis of morphological image processing technology , duplicate detection and leakage into account issues such as vehicles and road of the cross - lane vehicle video detection technology given the focus on research, design dynamically set algorithm based on virtual detection line lane , and Matlab simulation experiments achieved more the desired effect. The dynamic set of algorithms based on virtual detection line of the lane on the basis of the morphological denoising , according to the detection line of the width of the vehicle through the detection line divided , each division of the detection lines is vehicle is through the lane . In view of the lane is a dynamic setting , the recognition algorithm and Road vehicles traveling can be accurately detected and Road vehicles traveling and not missed , get rid of some of the detection algorithm by lane restrictions drawbacks . Meanwhile, if the detection lines is set sufficiently wide , can reduce the repeat count of the vehicles traveling on the cross track , to help improve the detection accuracy of the traffic volume . In addition, combined with the characteristics of a sequence of images of the moving target in the analysis of the flow detection technique based on the absolute value of the difference image using scaling method , in order to highlight the differences between the images ; introduces maximum variance threshold method and grayscale valve value combined binarization algorithm , for the extracted moving target ; lane dynamic set algorithm provided within the cavity and transverse direction of the image of the concave filling algorithm , both for dynamic algorithm based on the detection line of the lane to provide a reliable support.

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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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