线性判别分析在数字识别中的应用

O. P. Jena, S. Pradhan, P. Biswal, Sradhanjali Nayak
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引用次数: 9

摘要

近年来,字符识别由于在多个领域有着广泛的应用而引起了研究人员的极大关注。将输入的文本图像转换成机器可理解的代码或文本的过程称为光学字符识别。本文利用线性判别分析给出了一种有效的数字识别OCR方法,并与主成分分析结果进行了比较。最后,我们得出结论,由于降维,LDA比PCA具有更好的识别精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Linear Discriminant Analysis for Odia Numeral Recognition
In recent time the character recognition attract the attention of the researchers significantly as it has vast application in several fields. The process of converting input text images into machine understandable code or text is known as optical character recognition. In this paper we have devolved an efficient OCR for recognition of Odia Numerals using Linear Discriminant Analysis and compare the result with principal component analysis. Finally we conclude that LDA has a better recognition accuracy over PCA due to dimensionality reduction.
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