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作 者:曹月花 罗文广[1] 蓝红莉[2] 赵晓东[3] CAO Yuehua;LUO Wenguang;LAN Hongli;ZHAO Xiaodong(School of Electrical and Information Engineering,Guangxi University of Science and Technology,Liuzhou 545006,China;Center of Network and Modern Education Technology,Guangxi University of Science and Technology,Liuzhou 545006,China;State Grid Zhengzhou Power Supply Company,Zhengzhou 450001,China)
机构地区:[1]广西科技大学电气与信息工程学院,广西柳州545006 [2]广西科技大学网络与现代教育技术中心,广西柳州545006 [3]国家电网郑州供电公司,河南郑州450001
出 处:《现代电子技术》2017年第14期109-113,共5页Modern Electronics Technique
基 金:国家自然科学基金项目(61563006);广西汽车零部件与整车技术重点实验室基金项目(13-051-38);开放基金项目(2013KFZD03)资助
摘 要:针对不同光照、雨雪天、大雾天等恶劣环境下道路车道线识别难的问题,研究其识别算法。弱光照下,通过面积算子选取合适阈值进而实现边缘增强;夜间光照更弱的情况下,通过改进SUSAN算子实现夜间昏暗道路的边缘增强,解决了道路信息模糊、周围因素影响等造成的噪声干扰;强光照下,通过强光滤波算法可以消除伪边缘干扰,实现车道线的准确识别。雨雪天下,道路积水造成路面复杂,不能准确找到车道线特征点,通过建立路面积水反射模型,去除光的反射影响,增强路面和车道信息对比度,实现车道线信息的准确提取。大雾天,道路信息模糊不清,通过逆透视原理、差值分离建立道路识别模型,对道路特征进行加强分析,增强车道信息,提高识别效果。实验验证了所提出和改进的复杂环境下道路车道线识别算法的有效性,并且具有较强的鲁棒性和抗扰能力,可应用到智能交通系统中。It is difficult to recognize the lane line on road in the severe environments such as different illumination,rainday,snow day,fog day,etc,therefore a lane line identification algorithm is studied.Under the condition of weak illumination,the appropriate threshold is selected by means of area operator to realize the edge enhancement.Under the condition of weaker illumination at night,the SUSAN operator is improved to realize the edge enhancement of the dark road at night,and eliminatethe noise interference caused by fuzzy road information and surrounding factors.Under the condition of strong light,the highlight filtering algorithm can remove the pseudo edge interference,and realize the accurate recognition of the lane line.Under theconditions of snow or rain day,since the feature point of the lane line can′t be identified accurately because of the complex roadconditions caused by road water-logging,the reflection model of road water-logging was established to eliminate the influence oflight reflection,enhance the contrast of roads and lanes information,and extract the lane line information accurately.Under thecondition of fog day,because the road information is blur,the road recognition model based on inverse perspective principle anddifference separation was established to perform the enhancement analysis for road feature,enhance the lane information,and improve the recognition effect.The experimental results verify that the road lane line recognition algorithm is effective in complex environment,has strong robustness and anti-interference ability,and can be applied to the intelligent transportation system.
分 类 号:TN912.34-34[电子电信—通信与信息系统] TP391.41[电子电信—信息与通信工程]
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