电子学报2011，Vol.39Issue(5)：1121-1126,6.
一种基于类Haar特征和改进AdaBoost分类器的车辆识别算法
An Algorithm Based on Haar-Like Features and Improved AdaBoost Classifier for Vehicle Recognition
摘要
Abstract
An algorithm based on Haar-like features and AdaBoost classifier for vehicle recognition is proposed to solve the problem of poor recognition perfomance based on SVM (Support Vector Machines) classifier and cascaded AdaBoost classifier as well as the problem of much time consumed for traditional AdaBoost. At first,the extended Haar-like features are extracted using integral image method,then a small number of critical features from a very large set of Haar-like features are selected while training AdaBoost, finally two classes classification is performed using the AdaBoost classifier and the selected features. Experimental results demonstrate that the proposed approaches has better performance both in recognition and time consuming than traditional methods, and shows promising perspective.关键词
车辆识别/类Haar特征/AdaBoost算法Key words
vehicle recognition/ haar-like features/ AdaBoost algorithm分类
信息技术与安全科学引用本文复制引用
文学志,方巍,郑钰辉..一种基于类Haar特征和改进AdaBoost分类器的车辆识别算法[J].电子学报,2011,39(5):1121-1126,6.基金项目
国家863高技术研究发展计划项目(No.2006AA1Z221) （No.2006AA1Z221）
国家自然科学基金(No.60702076) （No.60702076）
南京信息工程大学科研基金资助项目(No.20100394) （No.20100394）
江苏高校优势学科建设工程资助项目 （）
