基于结构特征和词汇支持的手写体单词识别

Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings. Pub Date : 2003-08-03 DOI:10.1109/ICDAR.2003.1227727

E. Kavallieratou, K. Sgarbas, N. Fakotakis, G. Kokkinakis

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引用次数: 31

摘要

提出了一种基于结构特征、直方图和轮廓的手写体识别算法。众所周知的水平直方图和垂直直方图与新引入的径向直方图相结合，用于表示32 /spl乘以/ 32个字符矩阵的外向径向和外向径向轮廓，作为280维向量。识别过程由基于动态无循环有限状态自动机的词法组件支持。

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Handwritten word recognition based on structural characteristics and lexical support

In this paper a handwritten recognition algorithm based on structural characteristics, histograms and profiles, is presented. The well-known horizontal and vertical histograms are used, in combination with the newly introduced radial histogram, out-in radial and in-out radial profiles for representing 32 /spl times/ 32 matrices of characters, as 280-dimension vectors. The recognition process has been supported by a lexical component based on dynamic acyclic FSAs (Finite-State-Automata).

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Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.

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