计算机技术与发展2018，Vol.28Issue(3)：105-108,4.DOI:10.3969/j.issn.1673-629X.2018.03.022
基于并行组合分类器的脱机手写体数字识别
Off-line Handwritten Digit Recognition Based on Parallel Combined Classifiers
摘要
Abstract
In order to improve the recognition rate and reliability of off-line handwritten digit recognition,considering that traditional sin-gle classifiers have different sensitivity to the differences between digital,we propose a combined classifier of parallel organizational struc-ture combining three machine learning algorithms of K-nearest neighbor,general regression neural network and support vector machine. It uses the improved voting mechanism to determine the recognition result.Using MNIST database as data source,the comparable experi-ment on the performance of classifiers is carried out on MATLAB,whose results(recognition rate,rejection rate,false accept rate,relia-bility) are 97.48%,1.55%,0.97% and 99.02%.The experiments indicate that the parallel combined classifier is superior to the tradi-tional single classifier in terms of robustness,and other combined classifiers in terms of recognition rate,rejection rate and time complexi-ty.With a simple structure,it can achieve fast and efficient off-line handwritten digit recognition.关键词
模式识别/组合分类器/LR/广义回归神经网络/支持向量机/手写体数字Key words
pattern recognition/combined classifiers/LR/GRNN/SVM/handwritten digit分类
信息技术与安全科学引用本文复制引用
楚浩宇,高萌,刘永生..基于并行组合分类器的脱机手写体数字识别[J].计算机技术与发展,2018,28(3):105-108,4.基金项目
国家"863"高技术发展计划项目(2013AA10230304) （2013AA10230304）
