首页> 外文OA文献 >Spotting separator points at line terminals in compressed document images for text-line segmentation
【2h】

Spotting separator points at line terminals in compressed document images for text-line segmentation

机译:在压缩文档图像中的行终端处发现分隔符点,以进行文本行分割

摘要

Line separators are used to segregate text-lines from one another in document image analysis. Finding the separator points at every line terminal in a document image would enable text-line segmentation. In particular, identifying the separators in handwritten text could be a thrilling exercise. Obviously it would be challenging to perform this in the compressed version of a document image and that is the proposed objective in this research. Such an effort would prevent the computational burden of decompressing a document for text-line segmentation. Since document images are generally compressed using run length encoding (RLE) technique as per the CCITT standards, the first column in the RLE will be a white column. The value (depth) in the white column is very low when a particular line is a text line and the depth could be larger at the point of text line separation. A longer consecutive sequence of such larger depth should indicate the gap between the text lines, which provides the separator region. In case of over separation and under separation issues, corrective actions such as deletion and insertion are suggested respectively. An extensive experimentation is conducted on the compressed images of the benchmark datasets of ICDAR13 and Alireza et al [17] to demonstrate the efficacy.
机译:行分隔符用于在文档图像分析中将文本行彼此隔离。在文档图像的每个行终端处找到分隔符点将使文本行分割成为可能。特别是,识别手写文本中的分隔符可能是一件令人兴奋的事情。显然,在文档图像的压缩版本中执行此操作将具有挑战性,这是本研究提出的目标。这样的努力将避免为文本行分割而解压缩文档的计算负担。由于通常按照CCITT标准使用行程编码(RLE)技术压缩文档图像,因此RLE中的第一列将是白列。当特定行是文本行时,白列中的值(深度)非常低,并且在文本行分离点处的深度可能会更大。较大深度的较长连续序列应指示文本线之间的间隙,该间隙提供了分隔区域。如果出现过度分离和分离不足的问题,建议分别采取纠正措施,例如删除和插入。对ICDAR13和Alireza等人[17]的基准数据集的压缩图像进行了广泛的实验,以证明其有效性。

著录项

  • 作者

    Amarnath R.; Nagabhushan P.;

  • 作者单位
  • 年度 2017
  • 总页数
  • 原文格式 PDF
  • 正文语种
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号