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Skew estimation for scanned documents from 'noises'

机译:来自“噪声”的扫描文档偏斜估计

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The vast majority of the published skew estimation methods for scanned document images are for textual documents. These methods are based on the principle that the skew angles can be derived from the presence of the obvious text lines. The non-textual objects, such as line drawings, photographic inserts, scan artifacts including the dark bars around the borders and the center spine of bounded materials, and media contaminations are considered as "noises", thus are subject to elimination. Skew estimators that work in the presence of excessive noises are considered robust. This paper presents a skew estimation method that is based on the straight lines or edges. It uses the Muff Transform with a probe-line mapping scheme for feature identification. Various strategies for optimized line probing are devised. This method is applicable to both textual and graphical documents scanned with ordinary scanners or copiers under normal conditions. Selected images from the University of Washington English document image database I (UWDB-I) are used for its usability evaluation.
机译:已发布的针对扫描文档图像的偏斜估计方法绝大多数是针对文本文档的。这些方法基于这样的原理,即可以从明显的文本行的存在中得出偏斜角。非文本对象,例如线条图,照相插入物,扫描伪像(包括边界周围的黑条和边界材料的中心脊线)以及介质污染被视为“噪声”,因此可以消除。在存在过多噪声的情况下工作的偏斜估计器被认为是可靠的。本文提出了一种基于直线或边缘的偏斜估计方法。它使用带有探测线映射方案的Muff变换进行特征识别。设计了用于优化线路探测的各种策略。此方法适用于在正常情况下用普通扫描仪或复印机扫描的文本和图形文档。从华盛顿大学英语文档图像数据库I(UWDB-I)中选择的图像用于其可用性评估。

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