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Automatic rectification of warped Bangla document images

机译:自动校正扭曲的Bangla文档图像

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摘要

In this study, a robust algorithm for dewarping of camera-captured document images, mainly in Bangla script, is proposed. The algorithm can handle various types of warped document images and they are generated due to different types of document surfaces (convex, concave or multi-folded). The proposed algorithm is independent of font type, font size, font style and camera view angle. After initial preprocessing, the method first demarcates the text lines present in the document image. Then, the headline (shirorekha) position of each text line is estimated. Based on the headline position and shape, each text line is dewarped. If the document is highly warped, distorted text (e.g. thinner and shorter characters) is generated after dewarping. Special care has been taken to minimise this distortion based on most undistorted character information. Exhaustive testing shows the robustness and shape improvement of the proposed algorithm. Finally, for shape quality evaluation, some new measures are defined.
机译:在这项研究中,提出了一种鲁棒的算法,用于使相机捕获的文档图像变形(主要是在Bangla脚本中)。该算法可以处理各种类型的变形文档图像,并且它们是由于不同类型的文档表面(凸,凹或多重折叠)而生成的。所提出的算法与字体类型,字体大小,字体样式和相机视角无关。在初始预处理之后,该方法首先对文档图像中存在的文本行进行分界。然后,估计每个文本行的标题(shirorekha)位置。根据标题位置和形状,对每个文本行进行变形。如果文档高度变形,则在变形后会生成变形的文本(例如,较细和较短的字符)。基于大多数未失真的字符信息,已采取特殊措施来最小化此失真。详尽的测试表明了该算法的鲁棒性和形状改进。最后,为评估形状质量,定义了一些新措施。

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