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KSTRV1:一个场景文本识别数据集用于 (以阿拉伯语为基础) 脚本中部库尔德语

Sardar Omar Salih^1,2, Karwan Jacksi³

¹Web Technology Dept., Duhok Technical Institute, Duhok Polytechnic University, Duhok, Iraq.

|June 11, 2025

概括

本研究介绍了KSTRV1,这是库尔德语场景文本识别 (KSTR) 的新数据集. 它解决了当前资源中基于阿拉伯语的脚本的不足,使得低资源语言能够得到更好的认可.

科学领域:

计算机视觉计算机视觉
自然语言处理自然语言处理.
人工智能的人工智能

背景情况:

场景文本识别 (STR) 已经进步,但库尔德语等基于阿拉伯语的脚本在数据集中不足.
现有的资源缺乏足够的数据来为库尔德语等语言开发强大的STR模型.

研究的目的:

推出KSTRV1,这是库尔德语场景文本识别 (KSTR) 的第一个大型数据集.
解决STR研究中非拉丁字体资源稀缺的问题.
为低资源语言提供准确文本识别系统的开发提供便利.

主要方法:

创建KSTRV1数据集:1420个自然场景图像和19872个裁剪的单词样本.
包括库尔德语 (索拉尼语,巴迪尼语),阿拉伯语和英语文本.
产生了2万个合成文本实例,具有多种字体,定向和扭曲.

主要成果:

该数据集捕捉了库尔德斯坦地区的多语言景观,包括诸如遮蔽和照明变化等挑战.
详细的注释包括边界框,语言识别和文本定向标签.
KSTRV1提供了自然和合成数据,以支持强大的STR模型培训和评估.

结论:

KSTRV1显著增加了中库尔德语的资源,这是一个资源较低的语言.
该数据集预计将促进多语言STR,文档分析和光学字符识别 (OCR) 的研究.
公共可用性 KSTRV1 促进了更具包容性和准确的文本识别系统的发展.

关键词:

库尔德语场景文本识别 (KSTR)多语言文本识别系统自然景区的自然场景.非拉丁字母的OCR非拉丁字母的OCR.场景文本识别 (STR) 技术对于OCR的综合数据文本数据集是一个文本数据集.

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