Image-based field monitoring of Cercospora leaf spot in sugar beet by robust template matching and pattern recognition

Computers and Electronics in Agriculture

Volumn 116, Issue , 2015, Pages 65-79

  Zhou, Rong ^a   Kaneko, Shun'ichi ^a   Tanaka, Fumio ^b   Kayamori, Miyuki ^b   Shimizu, Motoshige ^b  

^a HOKKAIDO UNIVERSITY   (Japan)

^b HOKKAIDO RESEARCH ORGANIZATION   (Japan)

Author keywords

Foliar disease monitoring; Image processing; Machine learning; Pattern recognition; Sugar beets; Template matching

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUTTER (INFORMATION THEORY); IMAGE PROCESSING; LEARNING SYSTEMS; MOLASSES; OPTICAL CHARACTER RECOGNITION; PATTERN RECOGNITION; PLANTS (BOTANY); SUGAR BEETS; SUPPORT VECTOR MACHINES; TEMPLATE MATCHING;

DISEASE CLASSIFICATION; DISEASE MONITORING; FEATURE COMBINATION; FOLIAR DISEASE; ILLUMINATION CHANGES; ORIENTATION CODE MATCHING; PATTERN RECOGNITION METHOD; SPECULAR REFLECTIONS;

IMAGE MATCHING;

ALGORITHM; DISEASE INCIDENCE; FIELDWORK; FOLIAGE; FUNGAL DISEASE; IMAGE PROCESSING; LEAF; MACHINE LEARNING; MONITORING SYSTEM; PATTERN RECOGNITION; SUGAR BEET; SUPPORT VECTOR MACHINE;

BETA VULGARIS SUBSP. VULGARIS; CERCOSPORA;

EID: 84932619439     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2015.05.020     Document Type: Article

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