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Vehicle Flow Detection Algorithm and Implementation Based on Difference Image

Author: LiuZhangJun
Tutor: ZhangGeXiang
School: Southwest Jiaotong University
Course: Communication and Information System
Keywords: Intelligent Transportation Systems Hybrid difference image Flow detection Shape factor
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 102
Quote: 1
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Abstract


Intelligent transportation systems involves people traveling in various fields related to the efficiency of people travel. Traffic flow detection system is one of the subsystems of the intelligent transportation system. Traffic participants, managers provide the most basic data - the road traffic volume. The road traffic flow can be excavated road congestion, vehicle density, lane share information. Conventional suspension system - such as microwave, infrared, radar, and other detection systems and piezoelectric circuit permanently embedded systems, construction complex, not easy to maintain. With the development of information technology, based on the traffic flow detection system for image processing technology with information-rich detection, easy maintenance, simple installation, etc., gradually replacing the traditional traffic flow detection system. Traffic flow detection system based on image processing technology, and its core technology is the traffic flow detection algorithm. But not a common traffic flow detection algorithm, the countries in the world are depending on the traffic scene design traffic flow detection algorithm. Therefore, this paper were designed for highway traffic scene and a night-time traffic video toll station traffic flow detection algorithm. The main work and research of the thesis is as follows: 1, algorithm design highway hybrid differential. Environmental mutation detection algorithm using background subtraction algorithm, if there is environmental catastrophe is called inter-frame difference method detection; interframe difference and background subtraction method of combining the detection of environmental catastrophe did not happen; designing virtual detection zone set method and vehicle counting criteria to reduce the error caused by the vehicle blocked and vehicles change lanes. Video lane detection results show that the the hybrid differential algorithm is correct 95.45% undetected rate of 4.55%, are superior to the background subtraction. The false detection algorithm was 1.52%, the false detection rate of 19.7% better than the inter-frame difference method. 2, based on the principles of system availability, on the night-time traffic flow detection algorithm research, improved nighttime traffic flow detection algorithm based on feature recognition. The algorithm based on the vehicle virtual detection window width setting method to circumvent the pavement reflective; improved image calibration methods; introduced based on the connected region area and circular factors lights criterion to overcome the body reflective pavement reflectors detected with Halo headlights; removed by forcing the algorithm to avoid a repeat count of vehicles. The test results show that the improved the nightly traffic flow detection algorithm is correct rate of 94.44%, based lights pairing and trajectory tracking nighttime traffic flow detection algorithm results compared to detect the correct rate of 3.70%. 3, structured software design methods used in VC 6.0 platform the OpenCV library of night highway hybrid differential algorithm and improved traffic flow detection algorithm software.

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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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