Research of Sketch Symbol Recognition Based on Bayesian Network
Ding Qiu-lin · Manufacture Information Engineering of China · 2011
Because of a low accurative rate of sketch grouping and poor user-adaptive ability in most of sketch recognition algorithms,it proposes a method based on hybrid features of stroke used in sketches grouping.Based on the stroke sets obtained from first step,it builds a Bayesian network model for the user to identify the semantics of drawn sketches.This method groups the user-drawn sketches,makes each group represent a separated semantic symbol,and extracts feature vectors from the set of strokes.Finally,the semantics of the set corresponding to the symbol can be inferred through the Bayesian network model.The experiments verify that the method not only has a good ability in sketch grouping and symbol recognition,but also has a good adaptability of users,habits.