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Handwritten Word Recognition Using Multi-view Analysis

机译:使用多视图分析的手写单词识别

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摘要

This paper brings a contribution to the problem of efficiently recognizing handwritten words from a limited size lexicon. For that, a multiple classifier system has been developed that analyzes the words from three different approximation levels, in order to get a computational approach inspired on the human reading process. For each approximation level a three-module architecture composed of a zoning mechanism (pseudo-segmenter), a feature extractor and a classifier is defined. The proposed application is the recognition of the Portuguese handwritten names of the months, for which a best recognition rate of 97.7% was obtained, using classifier combination.
机译:本文为从有限大小的词典中有效识别手写单词的问题做出了贡献。为此,已经开发了一种多分类器系统,该系统可以从三个不同的近似级别分析单词,从而获得一种启发人类阅读过程的计算方法。对于每个近似级别,都定义了由分区机制(伪分段器),特征提取器和分类器组成的三模块体系结构。拟议的应用程序是对月份的葡萄牙语手写名称的识别,使用分类器组合可获得最佳识别率97.7%。

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