Rapid night vehicle detection method applied to self-adaptive high beam

Abstract

The invention discloses a rapid night vehicle detection method applied to a self-adaptive high beam, and the method comprises the steps: step 1, enabling an image collection module to collect a road traffic image in front of a vehicle, and transmitting image data information to an image processing module; step 2, processing the image data information by an image processing module, and judging a suspected vehicle lamp region by adopting a grid clustering algorithm; step 3, determining a halo range of a suspected vehicle lamp region by adopting a corrosion algorithm, calculating a halo color through a rapid algorithm, and judging a headlamp and a tail lamp; step 4, conducting pairing according to the geometrical relationship, recognizing vehicles, calculating vehicle coordinate position information and achieving night vehicle detection; and step 5, enabling a data transmission module to transmit the vehicle coordinate information calculated by the image processing module to the high beamcontrol module. The final vehicle lamp information obtained through image processing can serve as the control basis of the self-adaptive high beam lamp and can also provide support for other modulesneeding the vehicle lamp information.

Description

technical field [0001] The invention relates to the field of digital image processing, in particular to a fast nighttime vehicle detection method applied to adaptive high beams. Background technique [0002] As one of the important parts of the car, the high beam of the car mainly expands the field of vision at night or under poor lighting conditions and provides sufficient brightness. However, due to some reasons, such as the bad driving habits of the driver, or the novice driving the vehicle, the high and low beams cannot be switched in time when meeting cars at night, causing the other driver to be dazzled and unable to see the road conditions clearly, which is very likely to cause a car accident. Based on this, it is necessary to develop an adaptive high beam system, which can automatically detect the oncoming vehicle in the left lane and the vehicle in front of the current lane, automatically adjust the brightness of the high beam in the corresponding area, avoid dazzli...

AI Technical Summary

Problems solved by technology

[0006] According to the national standard, the high-beam and low-beam lights of automobiles are white, and the rear position lights are red. Judging headlights and taillights based on halo color, and solving the problems of long time-consuming image processing, low accuracy, and failure to meet real-time and accuracy requirements in current car light detection algorithms

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