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Pixel Probability Based Estimation of Skew Angle for Text Images

机译:基于像素概率的文本图像偏角估计

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The document reader reads the data from text document image for optical character recognition. If the image is rotated, it will not work properly. Some document images have a few degree of skew angle which creates difficulties in many other applications, so it is necessary to find out the skew angle of the digitalized document. This paper proposed an algorithm to automatically determine the skew angle of a text document image and produce a de-skewed image. The algorithm is based on the ratio of probability of the two binary pixels with the fact that rotated image matrix has higher order as compared to original image matrix and the ratio of probability of black pixels and white pixels changes. The algorithm is tested on more than 525 images taken from the IAM handwriting database [9] and on images generated by our self, for skew angle from -45° to +45° with 0.1° angle increment and found good angle estimation with mean error -0.0667° and variance = 1.3165°.
机译:文档阅读器从文本文档图像中读取数据以进行光学字符识别。如果旋转图像,它将无法正常工作。一些文档图像具有一定程度的歪斜角,这在许多其他应用中造成了困难,因此有必要找出数字化文档的歪斜角。本文提出了一种算法,可以自动确定文本文档图像的偏斜角并生成偏斜图像。该算法基于两个二进制像素的概率之比,与原始图像矩阵相比,旋转后的图像矩阵具有更高的阶数,并且黑色像素和白色像素的概率之比发生变化。该算法在IAM手写数据库[9]上拍摄的525幅以上图像以及我们自己生成的图像上进行了测试,其偏斜角从-45°到+ 45°(角度增量为0.1°),并且发现了良好的角度估计,且均值误差-0.0667°,方差= 1.3165°。

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