Citrus black spot detection using hyperspectral imaging

作     者：Daegwan Kim Thomas F.Burks Mark A.Ritenour Jianwei Qin 

作者机构：Asan Institute for Life SciencesAsan Medical CenterSongpa-guSeoul 138-736Korea Department of Agricultural&Biological EngineeringUniversity of FloridaGainesvilleFL 32611USA Indian River Research and Education Center(IRREC)University of FloridaFt.PierceFL 34945USA Environmental Microbial and Food Safety Laboratory(EMFSL)Agricultural Research ServiceU.S.Department of AgricultureBeltsvilleMD 20705USA 

出 版 物：《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报（英文）)

年 卷 期：2014年第7卷第6期

页      面：20-27页

核心收录：

学科分类：09[农学] 0902[农学-园艺学] 090201[农学-果树学] 

主　　题：citrus black spot hyperspectral imaging spectral angle mapper spectral information divergence imaging processing 

摘      要：This paper describes the development of a hyperspectral imaging approach for identifying fruits infected with citrus black spot(CBS).Hyperspectral images were taken of healthy fruit and those with CBS symptoms or other potentially confounding peel conditions such as greasy spot,wind scar,or *** angle mapper(SAM)and spectral information divergence(SID)hyperspectral analysis approaches were used to classify fruit samples into two classes:CBS or *** classification accuracy for CBS with SAM approach was 97.90%,and 97.14% with *** combination of hyperspectral images and two classification approaches(SID and SAM)have proven to be effective in recognizing CBS in the presence of other potentially confounding fruit peel *** study result can be a reference for the non-destructive detection of fruits infected with citrus black spot.