手写数字字符串分割和识别的新范例

Sungsoo Yoon, Yillbyung Lee, Gyeonghwan Kim, Yeongwoo Choi
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引用次数: 8

摘要

字符串识别是一个相当矛盾的问题,因为它需要将字符串分割成可理解的单元,但正确的分割需要先验的单元知识,这意味着识别能力。因此,为了解决这一困境,必须同时使用有意义单位的先验知识和分割方法,并且它们应该动态地相互作用。也就是说,将分割的结果作为基础信息来假设什么是最有可能的,然后利用其先验知识来帮助分割。这个模型使明确的分割不必要,因为它不推测可能的破发位置。它也可以识别一个数字,即使它包含不属于它的笔画。对属于NIST数据库的100个手写数字字符串使用此范式,识别率达到95%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New paradigm for segmentation and recognition of handwritten numeral string
String recognition is rather paradoxical problem because it requires the segmentation of the string into understandable units, but proper segmentation needs a-priori knowledge of the units and this implies a recognition capability. To solve this dilemma therefore, both a-priori knowledge of meaningful units and a segmentation method have to be used together, and they should dynamically interact with each other. In other words, the results of segmentation are used as fundamental information to suppose what is most likely to be, and then its a-priori knowledge is used to help the segmentation. This model makes explicit segmentation unnecessary because it does not speculate on possible break positions. It is also possible to recognize a digit even if it contains strokes that do not belong to to it. Using this paradigm for 100 handwritten numeral strings belonging to the NIST database has resulted in 95% recognition.
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