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《Computer Engineering and Applications》 2010-03
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Research on classification of wood texture based on feature level data fusion

WANG Hui,YANG Lin,DING Jin-hua School of Mechanical Engineering and Automation,Dalian Polytechnic University,Dalian,Liaoning 116034,China  
In order to enhance the precision of wood texture recognition,a kind of wood surface texture recognition method is proposed,which uses Gray Level Co-occurence Matrix(GLCM) and Gaussian-Markov Random Field(GMRF) on feature level data fusion.First,two sorts of feature parameters above are extracted respectively.Next,two sorts of texture features are fused on the feature level by simulated annealing algorithm.With the fused features,the recognition rate of the integrated BP neural network to the wood textural samples reaches to 97.00%.The result indicates that to recognize wood with the fused features is quite effective.
【Fund】: 黑龙江省自然科学基金No.C2004-03~~
【CateGory Index】: TP391.41
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