Automatic separation of words in multi-lingual multi-script Indian documents

U. Pal, B. B. Chaudhuri
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引用次数: 60

Abstract

In a multi-lingual country like India, a document may contain more than one script forms. For such a document it is necessary to separate different script forms before feeding them to OCRs of individual script. In this paper an automatic word segmentation approach is described which can separate Roman, Bangla and Devnagari scripts present in a single document. The approach has a tree structure where at first Roman script words are separated using the 'headline' feature. The headline is common in Bangla and Devnagari but absent in Roman. Next, Bangla and Devnagari words are separated using some finer characteristics of the character set although recognition of individual character is avoided. At present, the system has an overall accuracy of 96.09%.
自动分词在多语言多脚本印度文件
在像印度这样的多语言国家,一个文档可能包含不止一种脚本形式。对于这样的文档,有必要在将不同的脚本表单提供给单个脚本的ocr之前分离它们。本文描述了一种自动分词方法,该方法可以将单个文档中的罗马语、孟加拉语和德文加里语三种文字分离出来。该方法有一个树状结构,首先罗马文字使用“标题”特征分开。这个标题在孟加拉语和德文加里语中很常见,但在罗马语中却没有。接下来,使用字符集的一些更精细的特征将孟加拉语和德文加里语分开,尽管避免了对单个字符的识别。目前,该系统的总体准确率为96.09%。
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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