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An Efficient Primitive-Based Method to Recognize Online Sketched Symbols with Autocompletion

机译:一种有效的基于基元的自动完成符号识别在线草绘符号的方法

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We present a new structural method of sketched symbol recognition, which aims to recognize a hand-drawn symbol before it is fully completed. It is invariant to scale, stroke number, and order. We also present two novel descriptors to represent the spatial distribution between two primitives. One is invariant to rotation and the other is not. Then a symbol is represented as a set of descriptors. The distance between the input symbol and the template one is calculated based on the assignment problem. Moreover, a fast nearest neighbor (NN) search algorithm is proposed for recognition. The method achieves a satisfactory recognition rate in real time.
机译:我们提出了一种草绘符号识别的新结构方法,该方法旨在在手绘符号完全完成之前对其进行识别。比例尺,笔画编号和顺序不变。我们还提出了两个新颖的描述符来表示两个基元之间的空间分布。一个不变于旋转,另一个不变。然后,将符号表示为一组描述符。根据分配问题计算输入符号与模板之一之间的距离。此外,提出了一种快速最近邻搜索算法进行识别。该方法实时达到令人满意的识别率。

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