Research on the Variety Discrimination of Apple Using a Hybrid Possibilistic Clustering

摘要：

　　Near infrared reflectance (NIR) spectroscopy has been used to obtain NIR spectra of two varieties of apple samples.Thedimensionality of N IR spectra was reduced by principal component analysis (PCA),and discriminant information was extracted by linear discriminant analysis (LDA).Last,a hybrid possibilistic clustering algorithm (HPCA) was utilized as classifier to discriminate the apple samples of different varieties.HPCA integrates possibilistic clustering algorithm (PCA) and improved possibilistic c-means (IPCM) clustering algorithm,and produces not only the membership values but also typicality values by simple computation of the sample co-variance.Experimental results showed that HPCA,as an unsupervised learning algorithm,could quickly and easily discriminate the apple varieties.

关键词： Apple NIR Principal component analysis Hybrid possibilistic clustering

作者: WU Xiaohong CAI Tongxiang WU Bin SUN Jun

作者单位: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China Department of Information Engineering, ChuZhou Vocational Technology College, Chuzhou 239000, China

会议类型: 国际会议

会议名称: 2nd International Conference on Polymer Composities and Polymer Testing (2013第二届高分子复合材料与高分子测试国际会议暨先进工业技术与方案国际会议)(ISPCPT2013)

会议地点: 太原

会议语种:英文

页码: 668-671

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）