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首页> 外文期刊>Pattern Analysis and Machine Intelligence, IEEE Transactions on >The Effect of Border Noise on the Performance of Projection-Based Page Segmentation Methods
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The Effect of Border Noise on the Performance of Projection-Based Page Segmentation Methods

机译：边界噪声对基于投影的页面分割方法性能的影响

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摘要

Projection methods have been used in the analysis of bitonal document images for different tasks such as page segmentation and skew correction for more than two decades. However, these algorithms are sensitive to the presence of border noise in document images. Border noise can appear along the page border due to scanning or photocopying. Over the years, several page segmentation algorithms have been proposed in the literature. Some of these algorithms have come into widespread use due to their high accuracy and robustness with respect to border noise. This paper addresses two important questions in this context: 1) Can existing border noise removal algorithms clean up document images to a degree required by projection methods to achieve competitive performance? 2) Can projection methods reach the performance of other state-of-the-art page segmentation algorithms (e.g., Docstrum or Voronoi) for documents where border noise has successfully been removed? We perform extensive experiments on the University of Washington (UW-III) data set with six border noise removal methods. Our results show that although projection methods can achieve the accuracy of other state-of-the-art algorithms on the cleaned document images, existing border noise removal techniques cannot clean up documents captured under a variety of scanning conditions to the degree required to achieve that accuracy.
机译：投影方法已用于分析双色调文档图像以完成不同任务（例如页面分割和歪斜校正）超过二十年了。但是，这些算法对文档图像中边界噪声的存在很敏感。由于扫描或复印，边框噪声会沿着页面边框出现。多年来，文献中已经提出了几种页面分割算法。这些算法中的一些由于其相对于边界噪声的高精度和鲁棒性而被广泛使用。本文在这种情况下解决了两个重要问题：1）现有的边界噪声消除算法是否可以将文档图像清理到投影方法所需的程度，以达到竞争性能？ 2）对于已成功消除边界噪声的文档，投影方法能否达到其他最新页面分割算法（例如Docstrum或Voronoi）的性能？我们使用六种边界噪声消除方法对华盛顿大学（UW-III）数据集进行了广泛的实验。我们的结果表明，尽管投影方法可以在清洁后的文档图像上达到其他最新算法的精度，但是现有的边界噪声消除技术无法将在各种扫描条件下捕获的文档清除到达到该水平所需的程度。准确性。

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