基于场景使用的全局-局部结构方法的符号识别,并使用数据的XML表示

Mathieu Delalandre, Stéphane Nicolas, É. Trupin, J. Ogier
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引用次数: 6

摘要

本文研究了文献符号的结构识别问题。我们的系统是基于本地和全球结构方法的结合。全局方法根据一些紧密性和连接约束将连接的组件分组在一起。局部方法将每个连接的组件分割成几何对象(向量、弧、曲线)的图形。通过结构分类器对提取的图进行匹配,该分类器允许图-子图和精确-不精确匹配。通过场景使用,获得了系统的适应性。使用XML数据表示,允许数据操作和结果的图形表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Symbols recognition by global-local structural approaches, based on the scenarios use,and with a XML representation of data
This paper deals with the structural recognition ofsymbols on the documents. We have based our system ona combination of local and global structural approaches.The global approach groups the connected componentstogether according to some closeness and connectionconstraints. The local approach splits up each connectedcomponent into a graph of geometrical objects (vectors,arcs, curves). The extracted graphs are matched thanks toa structural classifier, which permits graph-subgraph andexact-inexact matching. The system adaptability isobtained thanks to the scenarios use. A XML datarepresentation is used, allowing the data manipulationsand the graphic representations of results.
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