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首页> 外文期刊>電子情報通信学会技術研究報告. 画像工学. Image Engineering >Learning pseudo Bayes discriminant method based on utilizing difference distribution of feature vectors
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Learning pseudo Bayes discriminant method based on utilizing difference distribution of feature vectors

机译:利用特征向量的差分分布学习伪贝叶斯判别方法

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摘要

We developed a learning pseudo Bayes discriminant method, that dynamically adapts a pseudo Bayes discriminant function to a font and image degradation condition present in a text. In this method, the characteristics of character pattern deformations are expressed as a statistic of a difference distribution, and information represented by the difference distribution is integrated into the pseudo Bayes discriminant function. The formulation of integrating the difference distribution into the pseudo Bayes discriminant function results in that a covariance matrix of each category is adjusted based on the difference distribution. We evaluated the proposed method on multi-font texts and degraded texts such as compressed color images and faxed copies. We found that the recognition accuracy of our method for the evaluated texts was much higher than that of conventional methods.
机译:我们开发了一种学习型伪贝叶斯判别方法,该方法可以动态地使伪贝叶斯判别函数适应文本中出现的字体和图像质量下降的情况。在该方法中,字符图案变形的特征被表示为差异分布的统计量,并且由差异分布表示的信息被集成到伪贝叶斯判别函数中。将差异分布整合到伪贝叶斯判别函数中的公式的结果是,基于差异分布调整每个类别的协方差矩阵。我们对多字体文本和降级文本(例如压缩彩色图像和传真副本)评估了该方法。我们发现,我们的方法对被评估文本的识别精度远高于传统方法。

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