基于二叉树和Adaboost算法的纸币号码识别

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.%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.