• Spectroscopy and Spectral Analysis
  • Vol. 30, Issue 2, 426 (2010)
FENG Jie1、*, LI Hong-ning1, YANG Wei-ping1, HOU De-dong1, and LIAO Ning-fang2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: Cite this Article
    FENG Jie, LI Hong-ning, YANG Wei-ping, HOU De-dong, LIAO Ning-fang. Horticultural Plant Diseases Multispectral Classification Using Combined Classified Methods[J]. Spectroscopy and Spectral Analysis, 2010, 30(2): 426 Copy Citation Text show less

    Abstract

    The research on multispectral data disposal is getting more and more attention with the development of multispectral technique, capturing data ability and application of multispectral technique in agriculture practice. In the present paper, a cultivated plant cucumber’ familiar disease (Trichothecium roseum, Sphaerotheca fuliginea, Cladosporium cucumerinum, Corynespora cassiicola, Pseudoperonospora cubensis) is the research objects. The cucumber leaves multispectral images of 14 visible light channels, near infrared channel and panchromatic channel were captured using narrow-band multispectral imaging system under standard observation and illumination environment, and 210 multispectral data samples which are the 16 bands spectral reflectance of different cucumber disease were obtained. The 210 samples were classified by distance, relativity and BP neural network to discuss effective combination of classified methods for making a diagnosis. The result shows that the classified effective combination of distance and BP neural network classified methods has superior performance than each method, and the advantage of each method is fully used. And the flow of recognizing horticultural plant diseases using combined classified methods is presented.
    FENG Jie, LI Hong-ning, YANG Wei-ping, HOU De-dong, LIAO Ning-fang. Horticultural Plant Diseases Multispectral Classification Using Combined Classified Methods[J]. Spectroscopy and Spectral Analysis, 2010, 30(2): 426
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