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- W2393782968 abstract "To solve the difficult problems of road congestion state detection,a road traffic state detection method based on machine vision is presented in this paper. Firstly,according to the design idea of points replacing surface,we customize the road areas and generate the uniform distribution of sampling points automatically,which contributes to reduce the computing and storage resources in embedded system. Secondly,the motionless existing sampling points reflecting the road congestion states are obtained by combining the background subtraction algorithm with the frame differential algorithm. Then,the vehicle model matching algorithm is presented to detect the congestion region and the queue length. The experiment results show that the proposed algorithm has high computational efficiency,less resource consumption,large detection range and strong robustness etc,and can quickly and accurately detect road congestion region and congestion states." @default.
- W2393782968 created "2016-06-24" @default.
- W2393782968 creator A5081690713 @default.
- W2393782968 date "2014-01-01" @default.
- W2393782968 modified "2023-09-26" @default.
- W2393782968 title "Research on Road Congestion State Detection Based on Machine Vision" @default.
- W2393782968 hasPublicationYear "2014" @default.
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