Weighted Hough transform on a gridded image plane

K. Sugawara
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引用次数: 8

Abstract

Detection of skews in input images is an important preprocess for analyzing document images. We propose a novel skew detection method based on vertical as well as horizontal splitting of an image. The center of gravity of the black pixels in each section is used as a sample point for performing the Hough transform, which gives the skew angle of the document image. We extend the Hough transform to incorporate the notion of weight, and apply it to reducing spurious line detection caused by the presence of large non text areas with many black pixels. The weighting function is defined according to the proportion of black pixels in the area, giving a low weight to an area with an extremely high proportion of black pixels. We conducted skew detection experiments on several document images. By using the Hough transform on connected components our method works four times faster than the conventional method and it has no restrictions on the detection range within which skew angles can be detected.
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网格图像平面上的加权霍夫变换
输入图像的倾斜检测是文档图像分析的重要预处理。我们提出了一种新的基于图像的垂直和水平分割的倾斜检测方法。每个部分中黑色像素的重心被用作执行霍夫变换的样本点,霍夫变换给出文档图像的倾斜角度。我们将霍夫变换扩展为包含权重的概念,并将其应用于减少由于存在大量黑色像素的非文本区域而导致的假线检测。权重函数是根据区域中黑色像素的比例来定义的,对于黑色像素比例极高的区域,权重较低。我们对一些文档图像进行了倾斜检测实验。通过对连通分量进行霍夫变换,该方法的检测速度比传统方法快4倍,并且对检测斜角的检测范围没有限制。
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