吉林大学学报(信息科学版) ›› 2020, Vol. 38 ›› Issue (2): 199-205.

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中文字符识别系统的研究与实现

王凌燕   

  1. 山西传媒学院 融媒技术学院,山西 晋中 303619
  • 收稿日期:2018-10-15 出版日期:2020-03-24 发布日期:2020-05-20
  • 作者简介:王凌燕(1983— ),女,山西忻州人,山西传媒学院讲师,主要从事数字媒体技术及数据分析应用研究,(Tel)86-13403468022(E-mail)63033233@ qq. com。
  • 基金资助:
    民族民间文化资源传承与开发利用技术集成与应用示范基金资助项目(2017YFB1402100)

Research and Implement of Chinese OCR System

WANG Lingyan   

  1. College of Media Technology,Communication University of Shanxi,Jinzhong 303619,China
  • Received:2018-10-15 Online:2020-03-24 Published:2020-05-20

摘要: 为提高字符识别率,将 DAG-SVM(Directed Acyclic Graph Support Vector Machine)算法应用于字符识别,
提出了一种基于 DAG-SVM 的 OCR(Optical Character Recognition) 中文字符识别系统,分别对图像预处理、
分割,字符识别 3 个模块进行了研究与实现。图像预处理采用图像滤波、灰度化处理、图像归正; 图像分割包
括二值化处理、横向及纵向分割; 字符识别模块对当前流行的三大类算法进行了研究,选用 DAG-SVM 作为字
符识别的算法,并基于 Matlab 进行了实现及验证。结果表明该系统 OCR 字符识别率达 92. 86%。

关键词: 图像预处理, 图像分割, 图像二值化, 字符识别, 支持向量机

Abstract:  In order to improve the recognition rate,the DAG-SVM(Directed Acyclic Graph Support Vector
Machine) algorithm is applied to character recognition,and an OCR(Optical Character Recognition) system
based on DAG-SVM,which can be divided into three components is proposed. Algorithms of image pre-
processing,image segmentation and OCR are researched. Image pre-processing,the first part,contains image
filtering,graying and tilt correction. And the second component is image segmentation,which contains
binaryzation and segmentation from two sides. The last part is character recognition,whose main algorithms is
researched and DAG-SVM is choosed. The system is simulated by Matlab,and the results show that the
recognition rate is 92. 86% .

Key words:  , image pre-processing, image segmentation, image binaryzation, character recognition, support
vector machine

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