Handwritten ZIP code Classification Using Artificial Neural Networks

被引：0
|
作者：
Kumar, K. Siva [1 ]
Devi, D. Uma [2 ]
机构：
[1] JNTU, Sri Mittapalli Coll Engn, Kakinada, India
[2] Sri Mittapalli Coll Engn, CSE Dept, Tummalapalem, Guntur, India
来源：
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2013年 / 13卷 / 08期
关键词：
ZIP code; Handwritten ZIP code; Pattern Recognition; Neural Network; Artificial Neural Network; Classification; NPR Tool; Slope correction and Slant correction;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new mechanism proposes the use of Artificial Neural Network (ANN) models for classifying handwritten zip-codes and also presents new techniques for to extract digits from zip-code images. Remove the slope and slant from handwritten zip-codes and normalize the size of Digit images with our proposed methods. Experiments have been conducted on handwritten ZIP codes and the classifying rates up to 99% achieved.
引用
收藏
页码：77 / 81
页数：5
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