一种新的车辆图像识别分类算法研究

重庆交通大学学报（自然科学版） ›› 2008, Vol. 27 ›› Issue (6): 1142-1145.

一种新的车辆图像识别分类算法研究

邓天民^1,2, 于勇¹, 邵毅明¹

1. 重庆交通大学交通运输学院, 重庆 400074;
2. 重庆大学自动化学院, 重庆 400044

收稿日期:2008-06-16 修回日期:2008-08-30 出版日期:2008-12-20 发布日期:2016-11-07
作者简介:邓天民(1979-),男,四川阆中人,讲师,博士研究生,主要从事图像处理、智能交通等研究;E-mail:dtianmin@gmail.com;Tel:13883782525。
基金资助:
重庆市科技攻关资助项目(CSTC2007AC6036);重庆市自然科学基金资助项目(CSTC2007BB6425)

A Novel Method of Vehicle Classification Based on Image Identification

DENG Tian-min^1,2, YU Yong¹, SHAO Yi-ming¹

1. School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China;
2. School of Automatization, Chongqing University, Chongqing 400044, China

Received:2008-06-16 Revised:2008-08-30 Online:2008-12-20 Published:2016-11-07

摘要/Abstract

摘要： 提出了一种在静止背景交通图像序列中运动车辆的检测和分类方法,即基于GVF-Snake模型和惯量椭圆的车辆分类算法。利用混和高斯模型(GMM)、期望最大化(EM)估计算法、改进GVF-Snake模型,从序列交通视频图像中检测出运动车辆;然后,借用刚体惯量椭圆原理,计算运动车辆等效椭圆偏心率,从而建立车长-车投影面积-车的等效椭圆偏心率三参数建立了车辆分类器。该方法的车辆检测与分类都是基于数理统计原理,算法复杂度小,可用数字逻辑编程实现,适合在嵌入式系统中应用。

关键词: 混和高斯模型(GMM), GVF-Snake模型, 偏心率

Abstract: A new approach is proposed to detect and classify the moving vehicle in static scenes,which is based on GVF-Snake model and inertia ellipse.The vehicles contour is extracted from successive traffic-frames by Gaussian Mixture Model,Expectation Maximization estimate algorithm and improved GVF-Snake model.The ellipse eccentricity of the moving vehicle is computed from the principal of inertia ellipse of rigid body.The vehicle classifier is established on the base of three parameters,which are the length of vehicle,the projection area of the vehicle and the equivalent ellipse eccentricity.As the method is based on the principles of statistics,it is quite simple and it can be easily programmed.This method is fit to be applied into the embed system.

Key words: GMM (Gaussian Mixture Model), GVF-Snake (Gradient Vector Flow-Snake) Model, eccentricity

中图分类号:

TP391.41

邓天民, 于勇, 邵毅明. 一种新的车辆图像识别分类算法研究[J]. 重庆交通大学学报（自然科学版）, 2008, 27(6): 1142-1145.

DENG Tian-min, YU Yong, SHAO Yi-ming. A Novel Method of Vehicle Classification Based on Image Identification[J]. Journal of Chongqing Jiaotong University(Natural Science), 2008, 27(6): 1142-1145.

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