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Symbol Recognition Combining Vectorial and Pixel-Level Features for Line Drawings

机译:结合矢量和像素级特征的线图符号识别

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In this paper, we present an approach for symbol representation and recognition in line drawings, integrating both the vector-based structural description and pixel-level statistical features of the symbol. For the former, a vectorial template is defined on the basis of the vectorization model and exploited in segmenting symbols from the line network. For the latter, a Radon-transform-based signature is employed to characterize shapes on the symbol and the components level. Experimental results on real technical drawings are presented to show the promising aspect of our approach.
机译:在本文中,我们提出了一种在线条图中用于符号表示和识别的方法,该方法集成了基于矢量的结构描述和符号的像素级统计特征。对于前者,在矢量化模型的基础上定义了矢量模板,并将其用于对线路网络中的符号进行分段。对于后者,采用基于Radon变换的签名来表征符号和组件级别上的形状。实际技术图纸上的实验结果表明了我们方法的前景。

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