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Adaptive document image binarization

机译:自适应文档图像二值化

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摘要

A new method is presented for adaptive document image binarization, where the page is considered as a collection of subcomponents such as text, background and picture. The problems caused by noise, illumination and many source type-related degradations are addressed. Two new algorithms are applied to determine a local threshold for each pixel. The performance evaluation of the algorithm utilizes test images with ground-truth, evaluation metrics for binarization of textual and synthetic images, and a weight-based ranking procedure for the final result presentation. The proposed algorithms were tested with images including different types of document components and degradations. The results were compared with a number of known techniques in the literature. The benchmarking results show that the method adapts and performs well in each case qualitatively and quantitatively. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 24]
机译:提出了一种用于自适应文档图像二值化的新方法,其中页面被视为子组件的集合,例如文本,背景和图片。解决了由噪声,照明和许多与光源类型相关的退化引起的问题。应用了两种新算法来确定每个像素的局部阈值。该算法的性能评估利用具有真实性的测试图像,用于文本和合成图像二值化的评估指标以及用于最终结果表示的基于权重的排序过程。所提出的算法已通过包含不同类型文档成分和降级图像的图像进行了测试。将结果与文献中的许多已知技术进行了比较。基准测试结果表明,该方法在每种情况下在定性和定量上均适应并表现良好。 (C)1999模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:24]

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