Bengali Handwriting Recognition and Conversion to Editable Text

Sadia Chowdhury, Farhan Rahman Wasee, M. S. Islam, Hasan U. Zaman
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引用次数: 2

Abstract

Handwriting recognition has been a very active field of research in the past few years in different sectors. Analyzing and deducing information from various handwritings can help to tackle many ongoing issues. Though extensive work has been done for English handwritings, any progress can hardly be seen in other languages like Bengali. Hence in this paper, a system has been proposed that takes a scanned image of Bengali handwritten text as its input and after processing it gives an editable version of that text. The system consists of many phases which mainly conducts image processing, machine learning by training the neural network and lastly identification of the Bengali characters. Several data and algorithms have been used to produce a thorough and accurate result.
孟加拉手写识别和转换到可编辑的文本
在过去的几年里,手写识别在各个领域都是一个非常活跃的研究领域。从各种笔迹中分析和推断信息可以帮助解决许多正在发生的问题。尽管在英语手写体方面做了大量的工作,但在孟加拉语等其他语言方面几乎看不到任何进展。因此,在本文中,提出了一种系统,该系统将孟加拉语手写文本的扫描图像作为其输入,并在处理后给出该文本的可编辑版本。该系统由多个阶段组成,主要进行图像处理,通过训练神经网络进行机器学习,最后进行孟加拉语字符的识别。几个数据和算法被用来产生一个全面和准确的结果。
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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