Image processing based degraded camera captured document enhancement for improved OCR accuracy

Pooja Sharma, Shanu Sharma
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引用次数: 9

Abstract

Over the past decade the document analysis and processing related to camera based document images has gained the interest of research community. Nowadays, cameras are easily available in the smart phones that can be carried in the small space of our pockets while being lightweight, portable and relieving us from the burden of walking down to a scanner for a digital copy of a document. But even though capturing a document image through a phone camera appears simple, the chances of obtaining a perfect picture are scanty. As when the picture is captured in an unconstrained environment, there are chances of degradation to creep in that will hamper the visual quality of the document image which further effect the readability(in terms of OCR accuracy). Low quality documents give poor results. Document images contain various degradations such as blur, uneven illumination, perspective distortion, low resolution, smear etc. Quality enhancement is helpful to recognize a camera captured document more accurately and if not completely removing the degradations, it can be used for suppressing them and making the text more readable. This paper evaluates the performance of various deblurring techniques for noisy and blurred camera captured documents.
基于图像处理的退化相机捕获文档增强,提高OCR精度
近十年来,基于相机的文献图像分析与处理引起了学术界的广泛关注。如今,相机很容易在智能手机中获得,可以在我们口袋的小空间中携带,同时重量轻,便携,减轻了我们走到扫描仪前获取数字文件副本的负担。但是,尽管通过手机相机拍摄文档图像看起来很简单,但获得完美照片的机会却很少。当在不受约束的环境中捕获图片时,有可能会出现退化,这会影响文档图像的视觉质量,从而进一步影响可读性(就OCR精度而言)。低质量的文档会产生糟糕的结果。文档图像包含各种退化,如模糊,光照不均匀,透视失真,低分辨率,涂抹等。质量增强有助于更准确地识别相机捕获的文档,如果不能完全消除降级,则可以用于抑制它们并使文本更具可读性。本文评估了各种去模糊技术对噪声和模糊相机捕获文档的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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