基于Haar-like和MB-LBP特征分区域多分类器车辆检测

Sub-regional and Multi-classifier Vehicle Detection Based on Haar-like and MB-LBP Features

高级辅助驾驶系统中的预碰撞系统不仅需要检测前向车辆,预防追尾碰撞,同时需要检测临近车道斜侧向车辆,实现对其潜在换道、合流行为的预测,提供实时的预警功能.文中提出分区域融合多种特征的车辆检测方法,解决前向车辆特征与斜侧向车辆特征存在明显差异的问题.同时,文中方法分别检测远近不同的车辆,进行不同程度的图像降采样,提高检测系统的实时性.多种交通场景的实地测试表明,文中方法可以实时、稳定、准确地检测到前向车辆和斜侧向车辆,在行车环境良好的情况下,具有较高的召回率和准确率.

The pre-collision system in the advanced vehicle-assisted driving system serves to detect both the forward vehicle to prevent the rear-end collision and the adjacent lane oblique lateral vehicle to realize the forecast of its potential lane change and confluence behavior, providing real-time warning function. In this oaoer, a method of vehicle detection with multiole characteristics of sub-region fusion is nronosed tosolve the obvious differences between forward vehicle and oblique lateral vehicle. The proposed method is utilized to detect the vehicles at different distances, respectively, to conduct image downsampling with different degrees. Consequently, the real-time performance of the detection system is improved. The field test of various traffic scenes indicates that the proposed method can detect the forward vehicle and the oblique side vehicle stably and accurately in real time. In good driving environment, the proposed method can achieve high recall rate and accuracy rate.