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Ruled lines detection and removal in grey level handwritten image documents

机译:绘制线路检测和灰级手写图像文档中的删除

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Converting Handwritten documents to its machine written counterpart using Optical Character Recognition has many benefits like easier formatting, less storage apace, and automatic translation if needed. However, it has many noise difficulties; one of them is the ruled lines intersection with the text. In this paper, we introduce a trial to detect these ruled lines and remove them without affecting the text strokes significantly in grey-level image documents. The detection stage use Hough Transform in four squared sub-windows. And the removal stage employs intensity histogram and its entropy to isolate the text. The removal stage is followed by a morphological based enhancement for the resulting text. The proposed technique has been tested on several test real-world image documents and achieved very good results.
机译:使用光学字符识别将手写文档转换为其机器书面对应物具有许多优势,如更容易格式化,更少的存储APACE和如果需要自动转换。但是,它有许多噪音困难;其中一个是与文本交叉的统治线条。在本文中,我们介绍了一种试验来检测这些统治线路,并在灰度图像文档中显着影响文本中风。检测阶段使用霍夫变换在四个方形窗口中。并且去除阶段使用强度直方图及其熵来隔离文本。除去阶段之后是由所得文本的基于形态的增强。所提出的技术已经在几个测试现实世界图像文件上进行了测试,并取得了非常好的结果。

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