文本行识别中多分类器系统的早期特征流集成与决策级组合

Roman Bertolami, H. Bunke
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引用次数: 13

摘要

本文比较了两种不同的结合特征流的方法来提高离线手写文本行识别系统的性能。这两种方法都结合了基于像素的特征流和几何特征流。第一种方法在早期阶段集成特征流,而第二种方法在决策级应用组合步骤。在实验中,早期集成方法优于决策级组合以及从单个特征流构建的识别器
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Early feature stream integration versus decision level combination in a multiple classifier system for text line recognition
This paper compares two different methods to combine feature streams to improve the performance of offline handwritten text line recognition systems. In both methods a pixel-based and a geometric feature stream are combined. The first method integrates the feature streams at an early stage whereas in the second method a combination step at the decision level is applied. In the experiments, the early integration approach outperforms the decision level combination as well as recognisers built from the individual feature streams
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