识别相对较小的手写字符或“大小问题”

V. Mazalov, S. Watt
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引用次数: 1

摘要

基于形状的在线手写识别在小字上很困难,因为这种识别的变形和变化通常与字符本身的大小相称。这个问题在角色大小不同且没有绝对比例的情况下更加突出。我们提出了使用尺寸信息来调整基于形状的分类的方法,以适当地考虑这种现象。这些方法可以被认为是基于大小的特征空间中的预分类,并且本质上是通用的,避免了基于特定字符的手动调整启发式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of Relatively Small Handwritten Characters or "Size Matters"
Shape-based online handwriting recognition suffers on small characters, in which the distortions and variations are often commensurate in size with the characters themselves. This problem is emphasized in settings where characters may have widely different sizes and there is no absolute scale. We propose methods that use size information to adjust shape-based classification to take this phenomenon appropriately into account. These methods may be thought of as a pre-classification in a size-based feature space and are general in nature, avoiding hand-tuned heuristics based on particular characters.
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