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Investigation of binarization techniques for unevenly illuminated document images acquired via handheld cameras

机译:通过手持摄像机获取照明不均匀的文档图像的二值化技术的研究

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Cameras in handheld devices, i.e., mobile phones, have become the fastest and the easiest method for capturing document images. However, document images captured with handheld cameras have been rarely collected and investigated. Digitization of text from the captured images presents a challenge because these images are prone to non-uniform lighting, uneven illumination, skew and shadow. The objectives of this paper are first to provide a benchmark dataset of document images captured via modern handheld devices and, second, to evaluate several binarization methods (i.e., Niblack, Sauvola, Wolf, Nick and Bataineh) using this dataset and certain meaningful measurements. The results show that the Nick and Bataineh methods achieved the best results in the English Printed Document Images (EPDI) test, whereas the Nick and Sauvola methods surpassed the other methods in the Arabic Printed Document Images (APDI) test that consists of two decoration formats. The Nick method surpassed other methods in documents that did not contain Harakat, and Savoula surpassed other methods in documents that did contain Harakat.
机译:手持设备(即移动电话)中的相机已成为捕获文档图像的最快,最简单的方法。但是,用手持摄像机捕获的文档图像很少被收集和调查。从捕获的图像中对文本进行数字化带来了挑战,因为这些图像容易出现照明不均匀,照明不均匀,歪斜和阴影的情况。本文的目的是首先提供通过现代手持式设备捕获的文档图像的基准数据集,其次,使用此数据集和某些有意义的度量来评估几种二值化方法(即Niblack,Sauvola,Wolf,Nick和Bataineh)。结果表明,Nick和Bataineh方法在英语印刷文档图像(EPDI)测试中获得了最佳结果,而Nick和Sauvola方法在阿拉伯印刷文档图像(APDI)测试中优于其他方法,后者由两种装饰格式组成。 Nick方法超越了不包含Harakat的文档中的其他方法,而Savoula超越了不包含Harakat的文档中的其他方法。

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