Application of Genetic Algorithms to Feature Subset Selection in a Farsi OCR

被引：0
|
作者：
Soryani, M. [1 ]
Rafat, N. [1 ]
机构：
[1] Iran Univ Sci & Technol, Dept Comp, Tehran, Iran
来源：
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 18 | 2006年 / 18卷
关键词：
Feature Subset Selection; Genetic Algorithms; Optical Character Recognition;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Dealing with hundreds of features in character recognition systems is not unusual. This large number of features leads to the increase of computational workload of recognition process. There have been many methods which try to remove unnecessary or redundant features and reduce feature dimensionality. Besides because of the characteristics of Farsi scripts, it's not possible to apply other languages algorithms to Farsi directly, In this paper some methods for feature subset selection using genetic algorithms are applied on a Farsi optical character recognition (OCR) system. Experimental results show that application of genetic algorithms (GA) to feature subset selection in a Farsi OCR results in lower computational complexity and enhanced recognition rate.
引用
收藏
页码：113 / 116
页数：4
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