Paper
8 December 2011 Diagnosis method of cucumber downy mildew with NIR hyperspectral imaging
Youwen Tian, Tianlai Li, Lin Zhang, Xiaodong Zhang
Author Affiliations +
Proceedings Volume 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis; 80020U (2011) https://doi.org/10.1117/12.901527
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
This study was carried out to develop a hyperspectral imaging system in the near infrared (NIR) region (900-1700 nm) to diagnose cucumber downy mildew. Hyperspectral images were acquired from each diseased cucumber leaf samples with downy mildew and then their spectral data were extracted. Spectral data were analyzed using principal component analysis (PCA) to reduce the high dimensionality of the data and for selecting some important wavelengths. Out of 256 wavelengths, only two wavelengths (1426 and 1626nm) of first PC were selected as the optimum wavelengths for the diagnosis of cucumber downy mildew. The data analysis showed that it is possible to diagnose cucumber downy mildew with few numbers of wavelengths on the basis of their statistical image features and histogram features. The results revealed the potentiality of NIR hyperspectral imaging as an objective and non-destructive method for the authentication and diagnosis of cucumber downy mildew.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Youwen Tian, Tianlai Li, Lin Zhang, and Xiaodong Zhang "Diagnosis method of cucumber downy mildew with NIR hyperspectral imaging", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80020U (8 December 2011); https://doi.org/10.1117/12.901527
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KEYWORDS
Hyperspectral imaging

Near infrared

Principal component analysis

Imaging systems

Diagnostics

Algorithm development

Binary data

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