Fisher Linear Discriminant Analysis based Technique Useful for Efficient Character Recognition

Manjunath Aradhya, G. Kumar, S. Noushath, P. Shivakumara
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引用次数: 5

Abstract

This paper describes the character recognition process from printed documents containing Kannada and English text. Kannada is the fifth most popular language in India and English is the most popular language in the world. Kannada is the language spoken by more than 60 million people of South India and English is the second official language at various government organizations through out India. The proposed character recognizer is based on the Fisher linear discriminant (FLD) analysis. It is usually performed to investigate differences among multivariate classes, to determine which attributes discriminate the classes, and to determine the most parsimonious way to distinguish among classes. The proposed system is tested on various fonts, degraded characters, noisy characters of Kannada and English. The overall accuracy of the proposed system is 96.1%.
基于Fisher线性判别分析的有效字符识别技术
本文描述了从含有卡纳达语和英语文本的印刷文档中识别字符的过程。卡纳达语是印度第五大最流行的语言,英语是世界上最流行的语言。卡纳达语是印度南部6000多万人使用的语言,英语是印度各政府机构的第二官方语言。所提出的字符识别器基于Fisher线性判别分析。它通常用于调查多变量类之间的差异,确定区分类的属性,并确定区分类的最简便方法。对该系统进行了测试,测试对象包括各种字体、退化字符、加噪字符。该系统的总体准确率为96.1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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