DocumentCode :
2807675
Title :
Paper Cut-Out Patterns Recognition Based on Geometrical Features
Author :
Zhang, Xianquan ; Qin, Fangyuan ; Li, Guoxiang
Author_Institution :
Dept. of Comput. Sci., Guangxi Normal Univ., Guilin, China
fYear :
2009
fDate :
19-20 Dec. 2009
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, we investigate the geometrical shape of cut-out patterns and the classification techniques, then introduce the six geometry features definition, including shape-factor, complexity, extendability, eccentricity, solidity and modal-ratio and propose the application of BP neural networks to train, classify and identify the patterns. The proposed scheme has the advantages of classifying and identifying the excessive geometrical artistic deformations. Experimental results demonstrate the superiority of the pattern recognition and the algorithm is simpler and easier to implement.
Keywords :
art; backpropagation; computational geometry; neural nets; pattern classification; BP neural network; classification technique; geometrical artistic deformation; geometry features definition; modal-ratio; paper cut-out pattern recognition; shape complexity; shape-factor; Art; Computational geometry; Computer networks; Feature extraction; Feedforward neural networks; Image segmentation; Multi-layer neural network; Neural networks; Pattern recognition; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
Type :
conf
DOI :
10.1109/ICIECS.2009.5362811
Filename :
5362811
Link To Document :
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