Text Segmentation from Bangla Land Map Images

Samit Biswas, Amit Kumar Das, B. Chanda
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Abstract

Abstract Text segmentation from land map images is a non-trivial task as map components are interleaved and overlapped in a complex spatial form. The characters in a word in most of the Indic languages, including Bangla (the 6th most spoken language in the world), are connected through a headline (”matra” or ”shirorekha”) which makes the corresponding word a single component. It has been observed that the Delaunay triangulation (DT) forms a number of small triangles on the text regions compared to other regions of the map - a property very much discernible for Bangla (and some other Indic scripts) texts. This property is primarily exploited here to segment text from the complex background of the land map images. The proposed text segmentation approach is tested and compared with an existing method on a collected dataset of paper map images( containing Bangla, an Indian regional language texts) and the results are encouraging.
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孟加拉土地地图图像的文本分割
摘要土地地图图像的文本分割是一项非常重要的任务,因为地图成分在复杂的空间形式中相互交错和重叠。在大多数印度语言中,包括孟加拉语(世界上第六大语言),单词中的字符通过一个标题(“matra”或“shirorekha”)连接起来,这使得相应的单词成为一个单独的组成部分。据观察,与地图上的其他区域相比,Delaunay三角测量法(DT)在文本区域形成了许多小三角形——这一特性在孟加拉语(和其他一些印度文字)文本中非常明显。此属性主要用于从陆地地图图像的复杂背景中分割文本。在收集的纸质地图图像数据集(包含孟加拉语,一种印度地区语言文本)上,对所提出的文本分割方法进行了测试并与现有方法进行了比较,结果令人鼓舞。
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