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A handwritten Chinese character recognition system using hierarchical displacement extraction based on directional features

机译:基于方向特征的分层位移提取的手写汉字识别系统

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摘要

A recognition system using displacement extraction based on directional features is proposed for handwritten Chinese characters. In the system, after extracting the features from an input image, the displacement is extracted by the minimization of an energy functional. which consists of the Euclidean distance and the smoothness of the extracted displacement. The coarse--to--fine strategy is adopted to escape local minima and reduce computational costs. The statistical classification is performed based on the estimated variance. In addition, the smoothness of the extracted displacement is utilized. An improvement in recognition performance is achieved as compared with the method without displacement extraction.
机译:提出了一种基于方向特征的位移提取识别系统。在该系统中,从输入图像中提取特征后,通过最小化能量函数来提取位移。由欧几里得距离和提取位移的平滑度组成。采用从粗到精策略来逃避局部最小值并降低计算成本。基于估计的方差执行统计分类。另外,利用所提取的位移的平滑度。与没有位移提取的方法相比,实现了识别性能的提高。

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