[1]王 枚.基于主成分分析的目标确认方法及其在车标定位识别中的应用[J].南京理工大学学报(自然科学版),2009,(01):42-46.
 WANG Mei,WANG Guo-hong.Object Confirmation Method Based on Principle Component Analysis and Its Application in Vehicle-logo Location and Recognition[J].Journal of Nanjing University of Science and Technology,2009,(01):42-46.
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基于主成分分析的目标确认方法及其在车标定位识别中的应用
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2009年01期
页码:
42-46
栏目:
出版日期:
2009-02-28

文章信息/Info

Title:
Object Confirmation Method Based on Principle Component Analysis and Its Application in Vehicle-logo Location and Recognition
作者:
王 枚1 2 王国宏1
1. 海军航空工程学院电子信息工程系, 山东烟台264001; 2. 烟台职业学院图像处理研究所, 山东烟台264670
Author(s):
WANG Mei12WANG Guo-hong1
1.Department of Electronic and Information Engineering,Naval Aeronautical Engineering Institute,Yantai 264001,China;2.Laboratory of Image Processing,Yantai Vocational College,Yantai 264670,China
关键词:
主成分分析 似真度函数 目标确认 车标定位识别
Keywords:
principle component analysis plausibility function object confirmation vehicle-logo location and recognition
分类号:
TP391.41
摘要:
提出一种基于主成分分析的目标确认方法,解决小目标定位错误率高,并由此导致无效目标识别的问题。将已建好的目标模板看成一组随机向量,利用主成分分析得到一组特征目标;从原图像中检测可能目标,并将其映入特征目标空间进行重构;构造原目标与重构目标的似真度函数,根据该函数值可对检测目标进行确认或剔除,降低误定位率,确保了进入后续识别的目标为目标库中对象。将该方法应用在实测车辆图像车标定位识别测试,结果表明:与不使用似真度函数验证相比,目标定位准确度提高了16.5%;使用不变矩最小距离分类器进行车标识别,识别准确度比不
Abstract:
An object confirmation method based on principle component analysis(PCA)is presented to improve the accuracy of small object location and recognition.The object samples are regarded as a set of random vectors.A set of eigen-objects is given by PCA.The object reconstruction is executed by reflecting the located actual object to the eigen-space.The plausibility function is defined between original located object and reconstruction object and the function is used to confirm the true object or to delete the false object in order to reduce the false-alarm rate.Actual vehicle-logo images are used to test the method and the experiment shows that the accuracy of the object location is improved by 16.5 percent than the result without object confirmation.The invariant moment minimum distance classifier is used to complete the vehicle-logo recognition and the experiment result shows that the accuracy of the object recognition is improved by 20 percent.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金( 60541001) ; 全国优秀博士学位论文作者专项基金( 200443); 山东省高校优秀青年教师国内访问学者项目
作者简介: 王枚( 1969- ), 女, 博士生, 副教授, 主要研究方向: 图像处理及模式识别, E-m a il:wangme i336@ 163. com。
更新日期/Last Update: 2012-11-19