林业科学2013，Vol.49Issue(6)：122-128,7.DOI:10.11707/j.1001-7488.20130617
基于PCA+FisherTrees特征融合的木材识别
Wood Identification Based on Feature Fusion of PCA and FisherTrees
摘要
Abstract
A new efficient method based on feature fusion of PCA and FisherTrees for wood identification was proposed in this paper.Firstly,the training samples were projected into PCA and FisherTrees space respectively to form the PCA and FisherTrees features,then the two features were fused through three ways,i.e.arithmetic mean,swapping transposition mean and weighting mean.Finally,the feature fusion was applied to classify with different distance functions.The experimental results showed that the new method had a higher recognition rate and was more efficient compared with the tradition subspace methods.The best identification result could be obtained by features fusion of PCA and FisherTrees with swapping transposition mean and by the cosine distance function classifier.关键词
特征融合/主成分分析(PCA)/费舍尔树(FisherTrees)/木材识别Key words
feature fusion/ principle component analysis(PCA) / FisherTrees/ wood identification分类
农业科技引用本文复制引用
刘子豪,汪杭军..基于PCA+FisherTrees特征融合的木材识别[J].林业科学,2013,49(6):122-128,7.基金项目
国家自然科学基金项目(30972361) （30972361）
浙江省教育厅重大科研攻关项目(ZD2009002) （ZD2009002）
浙江省自然科学基金项目(Y13C160027) （Y13C160027）
浙江农林大学研究生科研创新项目(3122013240224). （3122013240224）
