Segmenting bangla text for optical recognition

Md. Abdus Sattar, K. Mahmud, Humayun Arafat, A. F. M. Noor, Uz Zaman
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引用次数: 9

Abstract

One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. Existence of different type of characters in the scanned documents is a major problem to design an effective character segmentation procedure. In this paper, a new technique is presented for identification and segmentation of Bengali printed characters. This paper focuses on the segmentation of printed Bengali characters for efficient recognition of the characters. Our Line segmentation success rate is 99.7 % for 1000 lines, we have tested. Our Word segmentation success rate is 99.8 % for 4900 words tested. From the experiment we noticed that isolated characters fall into isolated group in 99.50 % cases. Most of the errors come from connected characters and characters having tau in front of them as segmenting tau we take the help of width. From the experiment we noticed that most of the errors came from components having multi-touching points between two characters.
用于光学识别的孟加拉文本分割
光学字符识别(OCR)系统识别率低的一个重要原因是字符分割错误。扫描文档中不同类型字符的存在是设计有效字符分割程序的主要问题。本文提出了一种识别和分割孟加拉文字的新方法。本文主要研究印刷体孟加拉文字的分割问题,以实现孟加拉文字的高效识别。我们已经测试了1000条线的线分割成功率为99.7%。我们的分词成功率为99.8%,测试了4900个单词。从实验中我们发现,在99.50%的情况下,孤立字符属于孤立组。大多数错误来自于连接字符和前面有tau的字符,作为分割tau,我们利用宽度的帮助。从实验中我们注意到,大多数错误来自两个角色之间具有多触点的组件。
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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