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An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration

机译:基于自适应时长段估计的离线手写汉字识别方法

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摘要

This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments, which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string, and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration, and is very effective for the recognition of overlapped, broken, touched, loosely configured Chinese characters.
机译:本文提出了一种基于自适应持续时间的连续段合并的离线手写汉字识别方法。手写汉字字符串被划分为一系列连续的段,这些段被组合以在滑动窗口内执行相异性评估,该滑动窗口的持续时间通过评估的形状和上下文的集成而自适应地确定。估计手写汉字字符串的平均笔划宽度,并通过使用像素和笔划特征的集成找到一组候选字符分割边界。分割和识别的最终决定是在最小的算术平均差异下做出的。实验证明,所提出的自适应时长方法优于固定时长方法,对于识别重叠,折断,触碰,松散配置的汉字非常有效。

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