Application of fuzzy membership grade and feedback correction in night traffic video vehicle detection

A technology of fuzzy membership degree and vehicle detection, which is applied in traffic control systems, road vehicle traffic control systems, instruments, etc., can solve problems such as poor tracking results and achieve the effect of ensuring accuracy

Inactive Publication Date: 2013-12-11
TIANJIN POLYTECHNIC UNIV
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AI Technical Summary

Problems solved by technology

However, the currently proposed vehicle detection method based on the characteristics of vehicle lights, under com

Method used

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  • Application of fuzzy membership grade and feedback correction in night traffic video vehicle detection
  • Application of fuzzy membership grade and feedback correction in night traffic video vehicle detection
  • Application of fuzzy membership grade and feedback correction in night traffic video vehicle detection

Examples

Experimental program
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Embodiment Construction

[0053] The tracking method of the present invention is used to track 6 groups of vehicles under complex background conditions at night. The images were all taken by SONY HDR-550D camera in night mode, and the shooting environment took into account high density, high speed, rainy and snowy days, 1 or 2 headlights, and curves. The image pixels are 320*240. The experimental data of its detection, matching and tracking were counted, and the statistical results are listed in Table 1-3.

[0054] Table 1 Vehicle detection results

[0055]

[0056] Table 2 Car light pairing results

[0057]

[0058] Table 3 Vehicle Tracking Results

[0059]

[0060] It can be seen from the above data that the detection success rate of the six groups of images is between 88.13% and 92.37%, the matching success rate is between 80.00% and 88.89%, and the tracking accuracy rate is as high as 92.31%. It shows that the method in this paper has a good effect on headlight detection and vehicle tr...

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Abstract

The invention provides a night complex vehicle detection method. The method comprises: first extracting vehicle lamps by using the homomorphic filtering technology in a frequency domain and the orientation fuzzy technology in a time domain; then performing pairing on the vehicle lamps by using the statistics information of the successfully paired vehicle lamps and introducing a vehicle lamp pairing feedback correction mechanism herein so as to enable a pairing result to be more accurate; and at last tracking vehicles and introducing a vehicle tracking feedback correction mechanism so as to ensure a single corresponding locus for a single vehicle. The shielding problems are respectively handled by using the vehicle lamp pairing feedback correction mechanism for comparison and determination. By the application provided by the invention, higher-accuracy vehicle detection and tracking can be realized, and an overall tracking system has higher precision.

Description

technical field [0001] The present invention relates to a vehicle motion analysis method, specifically combining homomorphic filtering and azimuth fuzzy technology, and then using the fuzzy membership degree of features such as vehicles to track and pair car lights, and introducing a car light pairing feedback correction mechanism at the same time The pairing result is more accurate, and the occlusion problem is solved. Finally, the vehicle tracking is realized by using the paired lights. The vehicle tracking feedback correction module introduced here ensures that one vehicle has one trajectory. This method can realize accurate localization and tracking of driving vehicles in complex traffic videos at night. Background technique [0002] Vehicle motion analysis usually tracks the target vehicle to obtain information such as the vehicle's speed, displacement, trajectory, etc., which provides an important basis for traffic accident handling, violation analysis, and security cr...

Claims

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Application Information

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IPC IPC(8): G08G1/017
Inventor 汤春明聂美玲王金海苗长云韦然
Owner TIANJIN POLYTECHNIC UNIV
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