Hierarchical primitive shape classification based on cascade feature point detection for early processing of on-line sketch recognition

A new approach for on-line primitive shape classification for early processing of sketch recognition is proposed in this paper. Firstly, cascade feature point detection composed of three steps is implemented, which can remove noise effectively and retain the characteristic of the shape. Then a hierarchical primitive shape classification method is applied which has an active effect on discrimination. Sketch input is firstly determined as a close or non-close shape through the close/non-close shape judgement. Following that two SVM classifiers are utilized to determine the exact type with a combined feature based on velocity and turning angle being adopted to improve recognition accuracy. Finally, the experiments prove the effectiveness and efficiency of the proposed approach in robust early processing for freehand sketching.