基于弹性曲率匹配的在线字符识别

Jong-Hoon Ahn, Jihyun Lee, Jinsu Jo, Y. Choi, Yillbyung Lee
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引用次数: 6

摘要

提出了一种有效的在线字符识别方法。它包括两个步骤:曲率提取和曲率匹配。单笔画的在线信号是一个二维位置向量序列,而其曲率是一维的。弹性曲率匹配基本上是参考曲率与测试特征之间的一维到一维的匹配问题,曲率的一维性使得匹配问题比二维到二维的匹配更加快速和容易。最后给出了将其应用于在线数字识别的结果,并进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Character Recognition Using Elastic Curvature Matching
An efficient method for online character recognition is suggested. It consists of two steps: curvature extraction and curvature matching. The online signal with a single stroke is a sequence of two-dimensional positional vectors whereas its curvature is one-dimensional. Elastic curvature matching is basically a 1D-to-1D matching problem between curvatures of reference and test characters, and one-dimensionality of curvature makes the matching problem more quick and easy than 2D-to-2D matching. We show the results obtained from applying it to online digit recognition and discuss them.
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