CAJ | 학술논문

为帮助驾驶员发现目标车道侧后方车辆尤其是视野盲区内车辆,从而避免或减少换道过程中发生的交通事故,提出了日间在高速公路上识别侧后方车辆的新方法.根据路面灰度值,将日间图像分为正常光照和弱光照两类.由于车辆阴影的灰度小于路面平均灰度,根据两侧车道区域内存在的灰度突变确定出侧后方车辆的可能存在区域.对确定的区域采用相应的阈值分割方法进行图像分割.在对分割后的二值化图像去噪、边缘提取和细化,以及提取车辆直线水平边缘基础上,根据系列车辆统计获得的先验知识(车辆前车窗的大小及比例等)验证车辆的真实存在.试验结果表明,该算法具有较好的可靠性和鲁棒性.
위방조가사원발현목표차도측후방차량우기시시야맹구내차량,종이피면혹감소환도과정중발생적교통사고,제출료일간재고속공로상식별측후방차량적신방법.근거로면회도치,장일간도상분위정상광조화약광조량류.유우차량음영적회도소우로면평균회도,근거량측차도구역내존재적회도돌변학정출측후방차량적가능존재구역.대학정적구역채용상응적역치분할방법진행도상분할.재대분할후적이치화도상거조、변연제취화세화,이급제취차량직선수평변연기출상,근거계열차량통계획득적선험지식(차량전차창적대소급비례등)험증차량적진실존재.시험결과표명,해산법구유교호적가고성화로봉성.
A method for detection of backside vehicle on freeway in daytime was proposed to help the driver check the existence of backside vehicles in the target lane,especially those in the blind zones,and to reduce traffic accidents during lane changing.The road images are classified into two categories:taken under normal and weak illumination conditions according to their gray values.The possible backside vehicle is recognized if there is a sudden change in gray values within the area in the lanes of both sides because the gray values of vehicle shadows ale smaller than the average gray valueof the road surgace.The existence of backside vehicle is coatirmed by comparison between the ratios of windshield sizes extracted from the images with those in a list of the known vehicles after segmentations with different thresholds for normal and weak illumination conditions,denoising,and boundary extraction.Experimental results show that the proposed algorithm has good reliability and robustness.