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Volumn 2, Issue 3, 2008, Pages 168-177
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Citrus canker detection using hyperspectral reflectance imaging and PCA-based image classification method
a
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Author keywords
Canker; Citrus; Disease detection; Food safety; Hyperspectral imaging; Reflectance
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Indexed keywords
CANKER;
CITRUS;
CITRUS CROPS;
CITRUS FRUITS;
CLASSIFICATION ALGORITHMS;
CLASSIFICATION METHODS;
DISEASE DETECTION;
FOOD QUALITY;
FOOD SAFETY;
FRUIT QUALITY;
HYPER-SPECTRAL;
HYPERSPECTRAL IMAGE DATA;
HYPERSPECTRAL IMAGING;
HYPERSPECTRAL IMAGING SYSTEMS;
HYPERSPECTRAL REFLECTANCE;
IMAGE FEATURES;
MULTI-SPECTRAL IMAGING;
NEAR INFRA-RED REGION;
PRINCIPAL COMPONENT ANALYSIS (PCA);
REFLECTANCE;
REFLECTANCE IMAGING;
SAMPLE-HANDLING;
SHORT WAVELENGTHS;
SKIN CONDITIONS;
WAVELENGTH RANGES;
AGRICULTURAL PRODUCTS;
ATMOSPHERICS;
CANNING;
CLASSIFICATION (OF INFORMATION);
COMPETITION;
COPPER;
CORUNDUM;
DIGITAL IMAGE STORAGE;
EXTRACTION;
FEATURE EXTRACTION;
FINANCIAL DATA PROCESSING;
FOOD PRESERVATION;
FRUIT JUICES;
FRUITS;
IMAGE ANALYSIS;
IMAGE CLASSIFICATION;
IMAGE ENHANCEMENT;
IMAGE PROCESSING;
IMAGING SYSTEMS;
IMAGING TECHNIQUES;
INDUSTRIAL ECONOMICS;
LIGHT;
LIGHT SOURCES;
LIGHTING;
OPTICAL DATA PROCESSING;
OPTOELECTRONIC DEVICES;
REFLECTION;
THREE DIMENSIONAL;
WASTEWATER;
PRINCIPAL COMPONENT ANALYSIS;
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EID: 70350754467
PISSN: 19327587
EISSN: 19329954
Source Type: Journal
DOI: 10.1007/s11694-008-9043-3 Document Type: Article |
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Times cited : (107)
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References (17)
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