计算机工程与应用2013，Vol.49Issue(3)：202-206,5.DOI:10.3778/j.issn.1002-8331.1106-0580
基于主曲线算法的手写字符特征分析与提取
Analysis and extraction of structural features of off-line handwritten characters based on principal curves algorithm
马驰 1于淼2
作者信息
- 1. 北京科技大学经济管理学院,北京100083
- 2. 辽宁科技大学软件学院,辽宁鞍山114051
- 折叠
摘要
Abstract
Extraction and choice of features are critical factor to improving the recognition rate of off-line handwritten characters. Principal curves are nonlinear generalizations of principal components analysis. They are smooth self-consistent curves that pass through the "middle" of the distribution. They preferably describe the structural features of the data. Soft κ-segments algorithm of principal curves is used to extract the structural features of training data; the classification features used for characters coarse classification and precise classification are chosen by analyzing the structural features of principal curves in detail; coarse classification and precise classification are separately carried out in handwritten characters recognition. The CEDAR handwritten digit and letter database is used in the experiment. The result of the experiment shows that these features have good discriminating power of similar characters and the algorithm can effectively improve the recognition rate of off-line handwritten characters. The proposed method provides a new approach to the research for off-line handwritten characters recognition.关键词
主曲线/手写体字符识别/结构特征/特征选取Key words
principal curve/ off-line handwritten characters recognition/ structural features/ features extraction分类
信息技术与安全科学引用本文复制引用
马驰,于淼..基于主曲线算法的手写字符特征分析与提取[J].计算机工程与应用,2013,49(3):202-206,5.
