Segmentation of cursive text remains the challenging phase in the recognition of text. In OCR systems, the recognition accuracy of text is directly dependent on the quality of segmentation. In cursive text OCR systems, the segmentation of handwritten Urdu language text is a complex task because of the context sensitivity and diagonality of the text. This paper presents a line segmentation algorithm for Urdu handwritten and printed text and subsequently to ligatures. In the proposed technique, the counting pixel approach is employed for modified header and baseline detection, in which the system first removes the skewness of the text page, and then the page is converted into lines and ligatures. The algorithm is evaluated on manually generated Urdu printed and handwritten dataset. The proposed algorithm is tested separately on handwritten and printed text, showing 96.7% and 98.3% line accuracy, respectively. Furthermore, the proposed line segmentation algorithm correctly extracts the lines when tested on Arabic text.

中文翻译：

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一种有效的草书 OCR 斜线分割技术

草书文本的分割仍然是文本识别中具有挑战性的阶段。在 OCR 系统中，文本的识别准确率直接取决于分割的质量。在草书文本 OCR 系统中，由于文本的上下文敏感性和对角性，手写乌尔都语文本的分割是一项复杂的任务。本文提出了一种用于乌尔都语手写和印刷文本以及随后的连字的行分割算法。在所提出的技术中，采用计数像素方法进行修改的标题和基线检测，其中系统首先去除文本页面的偏斜度，然后将页面转换为行和连字。该算法在手动生成的乌尔都语打印和手写数据集上进行评估。所提出的算法分别在手写和印刷文本上进行了测试，分别显示了 96.7% 和 98.3% 的行精度。此外，当对阿拉伯文本进行测试时，所提出的行分割算法正确地提取了行。