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

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