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Recognition of rotated characters by the parametric eigen-space method

机译:参数特征空间法识别旋转字符

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摘要

In this paper, we present a method of recognizing inclined, rotated characters. First we construct an eigen sub-space for each category using the covariance matrix which is calculated from a sufficient number of rotated characters. Next, we can obtain a locus by projecting their rotated characters onto the eigen sub-space and interpolating between their projected points. An unknown character is also projected onto the eigen sub-space of each category. Then, the verification is carried out by calculating the distance between the projected point of the unknown character and the locus. This method has the added advantage of obtaining the recognition result (category) and angle of inclination at the same time. In our experiment, we obtained 99.89% of recognition rate.
机译:在本文中,我们提出了一种识别倾斜的旋转字符的方法。首先,我们使用协方差矩阵为每个类别构造一个特征子空间,该协方差矩阵是根据足够数量的旋转字符计算得出的。接下来,我们可以通过将其旋转字符投影到本征子空间上并在其投影点之间进行插值来获得轨迹。每个类别的本征子空间上也会投影一个未知字符。然后,通过计算未知字符的投影点与轨迹之间的距离来进行验证。该方法的另一个优势是可以同时获得识别结果(类别)和倾斜角度。在我们的实验中,我们获得了99.89%的识别率。

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