林业科学2011，Vol.47Issue(10)：141-145,5.
一种新的针叶材自动识别方法
A Novel Method of Softwood Recognition
摘要
Abstract
A novel method of softwood species computer automatic recognition through cross-sectional microscopic images is proposed in this paper. The method extracts PCA (principle component analysis) feature of wood images, generate "EigenTrees" , and then use SVM(support vector machine) to classify samples in feature space. Eight kinds of softwoods species, twelve samples in each species are used in our experiment. Using leave-one-out cross-validation (LOOCV) , wood recognition experiments are carried out under different conditions on image split methods, classification algorithms of nearest neighbor and SVM, and various norm distances. The results of these experiments show that wood recognition by parts of wood micro-texture is possible under certain conditions.关键词
主成分分析/支持向量机/计算机视觉/针叶材识别/特征树Key words
principle component analysis/support vector machine/computer vision/softwood recognition/EigenTrees分类
农业科技引用本文复制引用
汪杭军,汪碧辉..一种新的针叶材自动识别方法[J].林业科学,2011,47(10):141-145,5.基金项目
国家自然科学基金项目(60970082),浙江省自然科学基金项目(Y3090061,Y3080457),浙江省科技厅科研项目(2008C21087). （60970082）
