计算机应用 ›› 2011, Vol. 31 ›› Issue (02): 396-398.

• 模式识别 • 上一篇    下一篇

基于二叉树和Adaboost算法的纸币号码识别

潘虎1,陈斌1,李全文2   

  1. 1. 中国科学院成都计算机应用研究所
    2. 中国科学院成都分院计算机应用研究所
  • 收稿日期:2010-08-16 修回日期:2010-10-11 发布日期:2011-02-01 出版日期:2011-02-01
  • 通讯作者: 潘虎

Paper currency number recognition based on binary tree and Adaboost algorithm

  • Received:2010-08-16 Revised:2010-10-11 Online:2011-02-01 Published:2011-02-01
  • Contact: Hu PAN

摘要: 运用一种快速弱分类器训练算法和高速缓存策略来加速Adaboost算法的训练。集成学习算法Adaboost能够精确构建二分类器,运用二叉树型结构快速灵活地将纸币号码识别转化为一系列的Adaboost二分类问题。实验结果证明, 快速Adaboost训练算法能加快训练速度,基于二叉树和Adaboost的纸币号码识别系统具有较好的识别率和处理速度,已经应用在点钞机、清分机和ATM中。

关键词: Adaboost算法, 快速Adaboost算法, 二叉树, 号码识别

Abstract: A fast weak classifier training algorithm and a fast caching strategy were used to accelerate Adaboost training. Integrated learning algorithm Adaboost can accurately construct two classifiers, so paper currency number recognition was formulated as a series of Adaboost two-class classification problems quickly and flexibly by using binary tree structure. The experimental results demonstrate that the fast Adaboost training algorithm can speed up the training and the paper currency number recognition system based on binary tree and Adaboost algorithm has good recognition rate and processing speed, and it has widely been used in currency counter, cash sorter and ATM.

Key words: Adaboost algorithm, fast Adaboost algorithm, binary tree, number recognition