首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >SKEW CORRECTION OF DOCUMENT IMAGES BY RANK ANALYSIS IN FAREY SEQUENCE
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SKEW CORRECTION OF DOCUMENT IMAGES BY RANK ANALYSIS IN FAREY SEQUENCE

机译:票价序列排序分析的文档图像偏斜校正

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摘要

Skew correction of a scanned document page is an important preprocessing step in document image analysis. We propose here a fast and robust skew estimation algorithm based on rank analysis in Farey sequence. Our target document class comprises two major Indian scripts with headlines, namely Devnagari and Bangla. At the beginning, straight edge segments from the edge map of the document page are detected by our algorithm using properties of digital straightness. Straight edges derived in this manner are binned by Farey ranks in correspondence with their slopes. The principal bin, identified from these bins using the strength of accumulated edge points, represents the principal direction along the direction of headlines, from which the gross skew angle is estimated. A fast refinement algorithm is then applied with a finer tuning of Farey ranks, to detect the skew up to the desired level of precision. The algorithm has been tested on a diverse set of document images, containing Bangla and Devnagari scripts. Experimental results are quite encouraging in terms of accuracy, sensitivity to non-textual objects, effectiveness in dealing with unrestricted layouts, and computational efficiency.
机译:扫描文档页面的歪斜校正是文档图像分析中的重要预处理步骤。我们在此提出一种基于Farey序列秩分析的快速且鲁棒的偏斜估计算法。我们的目标文档类包括两个带有标题的主要印度文字,即Devnagari和Bangla。首先,我们的算法使用数字直线度的属性来检测文档页面边缘图的直线边缘段。以这种方式导出的直边由Farey等级与其坡度相对应。使用累积的边缘点的强度从这些垃圾箱中识别出的主要垃圾箱代表了沿标题方向的主要方向,据此可以估算出总体倾斜角。然后,通过对Farey等级进行更精细的调整来应用快速细化算法,以检测到所需精度水平的偏斜。该算法已在包含Bangla和Devnagari脚本的各种文档图像上进行了测试。从准确性,对非文本对象的敏感性,处理不受限制的布局的有效性以及计算效率方面来看,实验结果令人鼓舞。

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