[1]ZHAI Chuan-min,DU Ji-xiang,HUANG Fei.Graphic symbol recognition of engineering drawings based on radial basis probabilistic neural networks[J].CAAI Transactions on Intelligent Systems,2006,1(1):88-91.
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Graphic symbol recognition of engineering drawings based on radial basis probabilistic neural networks

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 1 Number of periods: 2006 1 Page number: 88-91 Column: 学术论文—机器感知与模式识别 Public date: 2006-03-25
Title:
Graphic symbol recognition of engineering drawings based on radial basis probabilistic neural networks
Author(s):
ZHAI Chuan-min1; DU Ji-xiang2; 3; HUANG Fei1
1.Department of Mechanical Engineering, Hefei University, Hef ei 230022,China; 2.Department of Computer,National Huaqi ao University, Quanzhou,362021,China; 3.School of information Science and techno logy, University of Science and Technology of China, Hefei,230026,China
Keywords:
radial basis probabilistic neural network;  graphicsy mbol;  engineering drawings recognition
CLC:
TP31
DOI:
-
Abstract:
A novel graphic symbol recognition approach of engineering drawings based on radial basis probabilistic neural network s (RBPNN) is proposed. The Hu invariant moment method is applied to extract the shape features of the segmented graphic symbol image of scanned engineering draw ings. The experimental results show that the RBPNN achieves a higher recognition rate and better classification efficiency with respect to radial basis function neural networks (RBFNN) and multi-layer perceptron networks (MLPN) for the gra phic symbol recognition task.
References:
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