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Symbol Recognition Combining Vectorial and Statistical Features

机译:矢量和统计特征相结合的符号识别

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In this paper, we investigates symbol representation introducing a new hybrid approach. Using a combination of statistical and structural descriptors, we overcome deficiencies of each method taken alone. Indeed, a Region Adjacency Graph of loops is associated with a graph of vectorial primitives. Thus, a loop is both representend in terms of its boundaries and its content. Some preliminary results are provided thanks to the evaluation protocol established for the GREC 2003 workshop. Experiments have shown that the existing system does not really suffer from errors but needs to take advantage of vectorial primitives which are not involved in the definition of loops.
机译:在本文中,我们研究了引入新的混合方法的符号表示。使用统计和结构描述符的组合,我们克服了每种方法单独使用的不足。实际上,循环的区域邻接图与矢量图元的图相关联。因此,循环在边界和内容方面都是代表。由于为GREC 2003研讨会制定了评估协议,因此提供了一些初步结果。实验表明,现有系统并没有真正遭受错误的困扰,但需要利用不涉及循环定义的矢量原语。

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