符号识别:认知方法

Rumaan Bashir, K. Giri
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引用次数: 0

摘要

计算机科学领域一直在解决与数据、信息、知识和智能领域相关的问题,显然是按时间顺序进行的。其中,符号识别问题受到了广泛的关注。分析和识别符号的过程包括多个阶段。针对符号识别的目的,已经设计和实现了许多算法,但通常集中在复杂的特征和属性上。在本文中,我们提出了一种使用最小数据量的离线机器绘制符号识别认知模型。该算法与符号的大小/倾斜度无关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Symbol Recognition: Cognitive Approach
The field of Computer Science has been solving issues related to the domains of data, information, knowledge and intelligence, obviously in a chronological manner. Among these the issue of Symbol Recognition has received lot of attention. The procedure of analyzing and recognizing symbols involves various stages. A number of algorithms have been devised and implemented for the purpose of symbol recognition but usually focus on complex features and properties. In this paper, we propose a cognitive model for the recognition of offline machine drawn symbols which uses minimal amount of data. The algorithm proposed is independent of the size/slant of the symbol.
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