[1]胡顾飞,严毅.基于Adaboost算法的车辆轮胎检测研究与实现[J].计算机技术与发展,2013,(09):227-229.
　HU Gu-fei[],YAN Yi[].Research and Realization on Vehicle Tire Detecting Based on Adaboost Algorithm[J].,2013,(09):227-229.
点击复制

基于Adaboost算法的车辆轮胎检测研究与实现()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年09期
页码:
227-229
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Research and Realization on Vehicle Tire Detecting Based on Adaboost Algorithm
文章编号:
1673-629X（2013）09-0227-03
作者:
胡顾飞1; 严毅2
[1]安徽理工大学 计算机科学与工程学院;[2]安徽理工大学 电气与信息工程学院
Author(s):
HU Gu-fei[1]; YAN Yi[2]
关键词:
轴距; Adaboost算法; OpenCV; 轮胎检测
Keywords:
wheelbase; Adaboost algorithm; OpenCV; tire detection
文献标志码:
A
摘要:
为了更有效地对路段车流的车型进行分类统计，可通过测量车辆轴距的方法实现归类。提出了一种基于Adaboost算法，利用OpenCV视觉库对摄像机采集的车辆图片进行轮胎识别的检测方法。其基本思想是建立轮胎样本和级联分类器，利用被训练成的强分类器对摄像机采集的视频截图进行目标车辆轮胎的检测，然后通过检测结果计算出车辆两个轮胎之间的距离参数，从而求出轴距以确定其车型。通过分析检测出来的轮胎图案，发现存在较高的漏检率和错检率。最后，通过调整样本结构，发现大幅提高了检测准确率
Abstract:
In order to undertake classification statistic to the traffic stream of space interval efficiently,it can be realized by measuring the wheelbase. A detection method of the tire identification based on Adaboost algorithm was proposed,using the OpenCV visual library on the vehicle images taken by the camera. The basic idea is to establish the vehicle tire samples and the cascade classifier,then to detect the vehicle tire from the video screenshots which taken by the camera with the strong classifier after training. Calculating the distance parame-ter by the detection results and obtaining the wheelbase to determine its models are the final steps. By analyzing the tire patterns detected, it is found that there is a high missing rate and false rate. Finally,the detection accuracy rating can be improved significantly by adjusting the sample structure

相似文献/References:

[1]郑诚 张瑞 陈娟娟.标记样本的Adaboost算法[J].计算机技术与发展,2008,(07):109.
　ZHENG Cheng,ZHANG Rui,CHEN Juan-juan.An Adaboost Algorithm with Sample Marked[J].,2008,(09):109.
[2]佘九华 王敬东 李鹏.基于Camshift的人脸跟踪算法[J].计算机技术与发展,2008,(09):12.
　SHE Jiu-hua,WANG Jing-dong,LI Peng.Face Tracking Algorithm Based on Camshift[J].,2008,(09):12.
[3]黄葛峰 吴忠 吴建国.基于人脸特征和Adaboost算法的人脸定位[J].计算机技术与发展,2012,(08):93.
　HUANG Ge-feng,WU Zhong,WU Jian-guo.Face Detection Based on Adaboost Algorithm and Facial Features[J].,2012,(09):93.
[4]朱银忠 胡剑凌.基于DM3730的人脸识别系统设计[J].计算机技术与发展,2012,(12):47.
　ZHU Yin-zhong,HU Jian-ling.Design of Face Recognition System Based on DM3730[J].,2012,(09):47.
[5]陈骁,金鑫. 基于级联Adaboost与示例投票的人脸检测[J].计算机技术与发展,2015,25(12):18.
　CHEN Xiao,JIN Xin. Face Detection Based on Cascade Adaboost and Exemplar Voting[J].,2015,25(09):18.
[6]王传钦[],曹江涛[],姬晓飞[]. 基于视频分析技术的车距测量及预警系统设计[J].计算机技术与发展,2016,26(09):87.
　WANG Chuan-qin[],CAO Jiang-tao[],JI Xiao-fei[]. Design of a Vehicle Distance Measurement and Early Warning System Based on Video Analysis Techniques[J].,2016,26(09):87.
[7]陈拥权,陈影,陈学三. 基于Adaboost分类器的车辆检测与跟踪算法[J].计算机技术与发展,2017,27(10):165.
　CHEN Yong-quan,CHEN Ying,CHEN Xue-san. A Vehicle Detection and Tracking Algorithm Based on Adaboost Classifier[J].,2017,27(09):165.

更新日期/Last Update: 1900-01-01