位平面分解和扫描n元分类器

Sanaul Hoque, K. Sirlantzis, M. Fairhurst
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引用次数: 9

摘要

本文描述了一种用于高性能离线手写字符识别应用的多分类器配置。除了传统的扫描n元组分类器(或n元组)实现外,还使用了另外三个n元组系统,这些系统使用一种新的分解技术从轮廓链编码中提取的二进制特征集进行训练。因此,所提出的方案所实现的总体准确性远远高于大多数其他可用的分类系统,并且增加的复杂性(超过传统的n-tuple系统)是最小的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bit plane decomposition and the scanning n-tuple classifier
This paper describes a multiple classifier configuration for high performance off-line handwritten character recognition applications. Along with a conventional scanning n-tuple classifier (or sn-tuple) implementation, three other sn-tuple systems have been used which are trained using a binary feature set extracted from the contour chain-codes using a novel decomposition technique. The overall accuracy thus achievable by the proposed scheme is much higher than most other classification systems available and the added complexity (over conventional sn-tuple system) is minimal.
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