The invention relates to the technical field of high beams, in particular to a deep learning-based high beam identification method, which comprises the following steps of: extracting characteristics of center brightness, edge symmetry, linear gradient and the like for representing light spot and halo image information, and judging the type of a vehicle lamp; extracting and classifying vehicle lampcategories based on a multi-target convolutional neural network, and achieving multi-task learning by using a deep learning algorithm; combining an improved DBSCAN algorithm and a least square methodto carry out fitting on the vehicle lamp category; predicting an inter-frame displacement limit value to adaptively generate a tracking search area, and optimizing a target matching function of adjacent frames to achieve multi-vehicle lamp tracking; after the high beam lamp is tracked for a certain distance, performing left and right lamp pairing through colinear constraint, and completing high beam lamp identification. Stray light interference is avoided, and the feature redundancy is reduced. Meanwhile, the single vehicle lamp is independently matched up and down, so that the influence of vehicle lamp refitting is avoided, and the recognition effect is remarkably improved by using a deep learning algorithm.
本发明涉及远光灯技术领域,具体涉及一种基于深度学习的远光灯识别方法,本发明提取表征光斑和光晕图像信息的中心亮度、边缘对称性、线性梯度等特征,判断车灯类别;基于多目标卷积神经网络对车灯类别提取与分类,使用深度学习算法实现多任务学习;利用改进DBSCAN算法与最小二乘法相结合对车灯类别进行拟合;预测帧间位移极限值以自适应生成跟踪搜索区域,最优化相邻帧目标匹配函数实现多车灯跟踪;跟踪远光车灯一定距离后,通过共线性约束进行左右车灯配对,完成远光灯识别。避免杂光干扰减少了特征冗余。减少了以往多目标跟踪的复杂度,同时单车灯上下独立匹配,不受车灯改装的影响。同时使用深度学习算法显著提高识别效果。
Deep learning-based high beam identification method
一种基于深度学习的远光灯识别方法
2021-03-12
Patent
Elektronische Ressource
Chinesisch
IPC: | G06K Erkennen von Daten , RECOGNITION OF DATA / B60Q ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL , Anordnung von Signal- oder Beleuchtungsvorrichtungen, deren Einbau oder Halterung oder deren Schaltkreise bei Fahrzeugen allgemein / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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