A Sketch Recognition Algorithm Based on Bayesian Network and Convolution Neural Network

被引:2
|
作者
Hou, Xiang [1 ]
机构
[1] Sichuan Univ Arts & Sci, Sch Intelligent Mfg, 519 Tashi Rd, Dazhou 635000, Sichuan, Peoples R China
关键词
Bayesian network; stroke grouping; convolution neural network; sketch recognition;
D O I
10.20965/jaciii.2019.p0261
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Most of the existing sketch recognition algorithms are used to restrict the user's drawing habits to achieve the stroke grouping and recognition. In order to solve the problem, a new sketch recognition algorithm based on Bayesian network and convolution neural network (CNN) is proposed. First, the input sketch is processed by Gaussian low-pass filter and a smoother stroke can be obtained. The stroke of continuous input is divided, then the Bayesian network and CNN are performed on stroke recognition respectively. The recognition result of Bayesian network is adopted when the reliability of stroke is larger than the threshold, otherwise recognition result of CNN will be adopted. The experiment result shows that the proposed algorithm is effective in circuit symbol recognition. The recognition rate was achieved 80.34% in the drawing process, and the final recognition rate was achieved 93.48%.
引用
收藏
页码:261 / 267
页数:7
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