西安电子科技大学学报（自然科学版）2017，Vol.44Issue(3)：89-95,7.DOI:10.3969/j.issn.1001-2400.2017.03.016
构建多部件关系概率模型的车辆检测方法
Vehicle detection using the location relationship model between multi-components
摘要
Abstract
In view of the complex traffic and changeable weather and illumination in a scene,traditional vehicle detection method based on the single part model may result in a bad detection.So,using the spatial location relationships existing in multi-components of the vehicle,license plate and rear lamps are selected to construct the probabilistic models,through which vehicles are detected in this paper.In the new method,first,the color image of the road video is decomposed to the rear lamp gray image and license plate gray image through a different color conversion model.After that,the further identification for the license plate is accomplished through the key steps of gradient feature extraction,regional gradient smoothing and local maximum gradient search;similarly,the further identification of rear lamps is accomplished through the key steps of threshold segmentation,connected domain analysis and area calculation.Finally,With the Gaussian Mixture Model,relationships between the parts of the probability are established,and for the relationship model,if it makes the likelihood probability greater than a preset threshold,we argue that these parts belong to the same vehicle,and take the test result as the final vehicle detection result.Experimental results indicate that the new vehicle detection method has a strong adaptability,which can perfectly deal with the bad illumination conditions and target occlusion conditions,as well as a variety of vehicle types.关键词
车辆检测/多部件模型/高斯混合建模/尾灯检测/车牌检测Key words
vehicle detection/part-based models/Gaussian mixture model/rear lamp detection/license plate detection分类
信息技术与安全科学引用本文复制引用
宋俊芳,宋翔宇,郭晓军,王卫星..构建多部件关系概率模型的车辆检测方法[J].西安电子科技大学学报（自然科学版）,2017,44(3):89-95,7.基金项目
国家自然科学基金资助项目(61572083) （61572083）
西藏科技厅自然科学基金资助项目(2015ZR-13-17) （2015ZR-13-17）
