Classification of African Mosaic Virus Infected Cassava Leaves by the Use of Multi-Spectral Imaging

作     者：Mama Sangare Thérèse Atcham Agneroh Olivier Kossan Bagui Issiaka Traore Abdramane Ba Jeremie Thouakesseh Zoueu 

作者机构：Laboratoire d’Optique de Spectroscopie et des Sciences de l’Atmosphere Université des Sciences Techniques et Technologies de Bamako (USTTB) Bamako Mali Laboratoire de Phytopathologie et Biologie Végétale Institut National Polytechnique Felix Houphouë t-Boigny Yamoussoukro Cote d’Ivoire Laboratoire d’Instrumentation Image et Spectroscopie Institut National Polytechnique Felix Houphouë t-Boigny Yamoussoukro Cote d’Ivoire 

出 版 物：《Optics and Photonics Journal》 (光学与光子学期刊（英文）)

年 卷 期：2015年第5卷第8期

页      面：261-272页

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：Classification Infected Leaves African Cassava Mosaic Virus Multispectral Imaging 

摘      要：In this work, we have used multispectral imaging technology to classify cassava leaves infected by African mosaic virus by the use of their unique spectral finger print. The spectra are extracted from transmission, reflection and diffusion of their multispectral images;they have been then analyzed with statistical multivariate analysis techniques. Principal component analysis (PCA) has been used followed by K-means and Ascending Hierarchical Classification (AHC) to endorse the classification. The contribution of this work is the use of multispectral imagery which binds both spatial and spectral information to differentiate and sort infected leaves. The results show that the multimodal and imaging spectroscopy may allow blind identification and characterization of infected leaves.