Character recognition using wavelet compression

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI:10.1109/ICCITECHN.2010.5723900

Hayder Ali, Y. Ali, Eklas Hossain, S. Sultana

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引用次数: 6

Abstract

The objective of this project is to build a character recognition system, which is able to recognize printed and handwritten character from A to Z. the typical optical character recognition systems, regardless the character's nature, are based mainly on three stages, preprocessing, features extraction, and discrimination. Each stage has its own problems and effects on the system efficiency which is the time consuming and the recognition errors. In order to avoid these difficulties this project presents new construction of character recognition tool using the technique similar to that is used in image compression such as wavelet compression or JPEG compression. Wavelet compression is chosen as the technique implemented for this project. Wavelet compression technique extracted the important coefficient from the images. The Euclidean distance between the coefficient of the test images and training images is computed. Character is considered recognized if the Euclidean distance calculated is smaller than the Global threshold value of 258. This character recognition system also has 18.81% of false rejection rate and 21.88% for false acceptance rate.

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小波压缩字符识别

本课题的目标是构建一个能够识别从a到z的印刷和手写字符的字符识别系统。典型的光学字符识别系统，无论字符的性质如何，主要是基于预处理、特征提取和识别三个阶段。每个阶段都有自己的问题和对系统效率的影响，主要是耗时和识别误差。为了避免这些困难，本项目提出了一种新的字符识别工具，使用类似于图像压缩的技术，如小波压缩或JPEG压缩。本课题采用小波压缩技术。小波压缩技术从图像中提取重要系数。计算了测试图像与训练图像系数之间的欧氏距离。如果计算的欧几里得距离小于全局阈值258，则认为特征被识别。该字符识别系统的错误拒绝率为18.81%，错误接受率为21.88%。

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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2010 13th International Conference on Computer and Information Technology (ICCIT)

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