An Improved Feature Extraction Method for Individual Offline Handwritten Digit Recognition

被引：4
|
作者：
Wang Qinghui [1 ,3 ]
Yang Aiping [2 ]
Dai Wenzhan [1 ]
机构：
[1] Zhejiang Sci Tech Univ, Dept Automat Control, Hangzhou 310018, Peoples R China
[2] Zhejiang Univ Finance & Econ, Hangzhou 310018, Peoples R China
[3] Longyan Univ, Dept Elect & Elect, Longyan 364000, Peoples R China
来源：
2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2010年
基金：
高等学校博士学科点专项科研基金;
关键词：
Offline handwritten digit recognition; feature extraction;
D O I：
10.1109/WCICA.2010.5554355
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Offline handwritten digit recognition (OHDR) is considered as one of difficult problems in the field of pattern recognition. Because it is a challenging computational problem mainly due to the vast differences associated with the handwritten patterns of different individuals. In this paper, a novel method of feature extraction is presented based on structural feature for OHDR by simulating the process of human recognizing handwritten digit. Firstly state and state value are introduced, then the steps of how to determine the eigenvalue is explained in detail, last the method is applied in OHDR, and the result show its effectiveness.
引用
收藏
页码：6327 / 6330
页数：4
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