TITLE:
Classification of African Mosaic Virus Infected Cassava Leaves by the Use of Multi-Spectral Imaging
AUTHORS:
Mama Sangare, Thérèse Atcham Agneroh, Olivier Kossan Bagui, Issiaka Traore, Abdramane Ba, Jeremie Thouakesseh Zoueu
KEYWORDS:
Classification, Infected Leaves, African Cassava Mosaic Virus, Multispectral Imaging
JOURNAL NAME:
Optics and Photonics Journal,
Vol.5 No.8,
August
31,
2015
ABSTRACT: 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.