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Touching text line segmentation combined local baseline and connected component for Uchen Tibetan historical documents
Information Processing & Management ( IF 7.4 ) Pub Date : 2021-07-27 , DOI: 10.1016/j.ipm.2021.102689
Pengfei Hu 1 , Weilan Wang 1 , Qiaoqiao Li 1 , Tiejun Wang 1
Affiliation  

The text lines of ancient Tibetan books are skewed and distorted, strokes are broken, and complex adjacent text lines touch each other, which makes text line segmentation extremely challenging. In this paper, a text line segmentation method based on local baselines and connected component allocation is proposed. First, the pseudotext line is detected by analyzing the horizontal projection, straight line detection and the average character height information, and then the local baseline position is determined in the pseudotext line area by the projection method. Second, the adhesion area detection is performed, which mainly includes the adhesion between characters and the adhesion between characters and strokes. The position relationship between the connected components is used to complete the adhesion between characters. A convolutional neural network is used to complete the adhesion between characters and strokes. Then, the watershed algorithm is used to segment touching connected components. Finally, the broken strokes are assigned to the text lines in which they belong according to the characteristics of Tibetan character structures. Subsequently, the assigned strokes are postprocessed to complete stroke correction, and finally the line segmentation is completed. Experiments show that this method can effectively reduce the influence of text line distortion and skew on text line segmentation, has a high degree of robustness, and has good segmentation accuracy for image text lines in Tibetan documents with touching and broken strokes.



中文翻译:

结合局部基线和连通分量的乌钦藏文历史文献的触摸文本行分割

藏文古籍文字行歪斜扭曲,笔画断断续续,复杂的相邻文字行相互接触,使得文字行分割极具挑战性。本文提出了一种基于局部基线和连通分量分配的文本行分割方法。首先通过分析水平投影、直线检测和平均字符高度信息检测伪文本行,然后通过投影方法确定伪文本行区域中的局部基线位置。其次,进行粘连区域检测,主要包括字符之间的粘连和字符与笔画之间的粘连。连接组件之间的位置关系用于完成字符之间的粘合。使用卷积神经网络来完成字符和笔画之间的粘合。然后,分水岭算法用于分割接触连接的组件。最后,根据藏文汉字结构的特点,将断笔划归入其所属的文本行。随后对指定的笔画进行后处理,完成笔画校正,最后完成线段分割。实验表明,该方法能有效降低文本行失真和歪斜对文本行分割的影响,具有较高的鲁棒性,对有笔触和断笔画的藏文文档中的图像文本行具有良好的分割精度。分水岭算法用于分割接触连接的组件。最后,根据藏文汉字结构的特点,将断笔划归入其所属的文本行。随后对指定的笔画进行后处理,完成笔画校正,最后完成线段分割。实验表明,该方法能有效降低文本行失真和歪斜对文本行分割的影响,具有较高的鲁棒性,对有笔触和断笔画的藏文文档中的图像文本行具有良好的分割精度。分水岭算法用于分割接触连接的组件。最后,根据藏文汉字结构的特点,将断笔划归入其所属的文本行。随后对指定的笔画进行后处理,完成笔画校正,最后完成线段分割。实验表明,该方法能有效降低文本行失真和歪斜对文本行分割的影响,具有较高的鲁棒性,对有笔触和断笔画的藏文文档中的图像文本行具有良好的分割精度。对指定的笔画进行后处理,完成笔画修正,最后完成线段分割。实验表明,该方法能有效降低文本行失真和歪斜对文本行分割的影响,具有较高的鲁棒性,对有笔触和断笔画的藏文文档中的图像文本行具有良好的分割精度。对指定的笔画进行后处理,完成笔画修正,最后完成线段分割。实验表明,该方法能有效降低文本行失真和歪斜对文本行分割的影响,具有较高的鲁棒性,对有笔触和断笔画的藏文文档中的图像文本行具有良好的分割精度。

更新日期:2021-07-27
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