迈向依赖于书写者的手写字符识别器

A. Navarro, C. R. Allen
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引用次数: 2

摘要

在字符分类之前对字符图像进行预处理是设计可靠的手写识别系统的关键步骤。但是,必须保留字符结构。提出了一种预处理算法,并将其应用于依赖于写作者的手写字符识别系统。预处理阶段提供了每个字符的中间轴多边形表示,保留了字符结构,并有效地减少了数据,而不会引入假肢,“颈”和马刺等伪影。这种简洁的字符表示允许恢复动态信息。描述了一种基于动态构件翘曲的动态特征提取器和统计分类器。第一选择识别率为91.67%,第二选择识别率为94.55%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a writer-dependent hand-written character recogniser
The pre-processing of character images prior to character classification is a crucial step in the design of a reliable handwriting recognition system. However, the character structure must be preserved. A preprocessing algorithm is presented and applied to a writer-dependent hand-written character recognition system. The pre-processing stage provides a medial axis polygonal representation of each character which preserves the character structure, and efficient data reduction, without introducing artifacts such as false limbs, "necking" and spurs. This clean character representation allows dynamic information to be recovered. A dynamic feature extractor and a statistical classifier based on dynamic component warping is described. Recognition rates of 91.67% (first choice) and 94.55% (second choice) have been achieved.
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