Using local maxima profile and Piece-Wise technique for line segmentation on Thai handwritten historical documents

Seksan Sangsawad, R. Chamchong, L. Fung
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引用次数: 1

Abstract

This paper presents a new approach for segmenting text lines on Thai handwritten documents. The proposed technique is based on an Adaptive Local Connectivity Map concept using Piece-Wise Separating Lines. The algorithm is designed to solve problems in handwritten documents such as fluctuating text lines. Moreover, local maxima projection profile is used for enhancing the speed of extraction. The proposed algorithm consists of four steps. Firstly, Otsu algorithm is used to binarize the source image. Second, Piece-Wise Separating Lines is applied to derive the Adaptive Local Connectivity Map to show mask text lines. In the third step, local maxima projection profile is used as a guideline for extracting text lines. Finally, contour algorithm is used to identify the interested mask text line. The interested mask text is used to map with text image in order to extract the text lines. Analysis of experimental results on the King Rama 5 archive data indicated that the method has achieved a correct rate of 85.7%.
利用局部最大轮廓和分段分割技术对泰国手写历史文献进行线段分割
本文提出了一种新的泰语手写文档文本行分割方法。所提出的技术是基于使用分段分隔线的自适应局部连接图概念。该算法旨在解决手写文档中的文本行波动等问题。此外,为了提高提取速度,还采用了局部最大投影轮廓。该算法包括四个步骤。首先,采用Otsu算法对源图像进行二值化处理。其次,应用分段分隔线导出自适应局部连通性映射来显示掩码文本行。第三步,利用局部最大投影轮廓作为提取文本线条的准则。最后,利用轮廓线算法对感兴趣的蒙版文本线进行识别。将感兴趣的掩码文本与文本图像进行映射,提取文本行。对国王拉玛5号档案数据的实验结果分析表明,该方法的正确率达到了85.7%。
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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