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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >AN APPROACH TO NATURAL STROKE EXTRACTION FOR OFF-LINE LOOSELY-CONSTRAINED HANDWRITTEN CHINESE CHARACTERS
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AN APPROACH TO NATURAL STROKE EXTRACTION FOR OFF-LINE LOOSELY-CONSTRAINED HANDWRITTEN CHINESE CHARACTERS

机译：离线松散约束手写汉字的自然笔画提取方法

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摘要

This paper proposes a new approach to extracting natural strokes from the skeletons of loosely-constrained, off-line handwritten Chinese characters. It admits the output sub-strokes from a previously proposed fuzzy substroke extractor as its inputs. By identifying a number of expected ambiguities which include mutual similarities, unstable touches and joint/cross distortions, fuzzy stroke models are constructed and a "hit-all" fuzzy stroke matching strategy is pursued. Fuzzy partitioning technique is used to generate a ranked list of consistent stroke sets from the set of fuzzy strokes being identified. With this approach, a maximum of 20 distinct natural stroke classes can be extracted from each input character, together with an estimate on the actual count of strokes which compose the character. Our system offers a number of performance tuning capabilities such as the computation of the fuzzy scores of each extracted stroke, the adjustment on the fuzzy stroke model parameters, and the potential of incorporating one's personal writing styles into our methodology.
机译：本文提出了一种从松散约束的离线手写汉字的骨架中提取自然笔画的新方法。它允许先前提出的模糊子笔画提取器的输出子笔画作为其输入。通过识别包括相互相似性，不稳定的触摸和关节/交叉失真在内的许多预期的歧义，构建了模糊笔划模型，并寻求了“全面”的模糊笔划匹配策略。模糊划分技术用于从要识别的模糊笔划集合中生成一致笔划集的排序列表。使用这种方法，最多可以从每个输入字符中提取20种不同的自然笔画类别，并估算出构成该字符的笔画的实际笔数。我们的系统提供了许多性能调整功能，例如计算每个提取笔划的模糊分数，对模糊笔划模型参数进行调整以及将个人写作风格纳入我们的方法中的潜力。

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