Publication | Closed Access
DETECTION OF INSECTS IN BULKWHEAT SAMPLES WITH MACHINE VISION
88
Citations
6
References
1998
Year
EngineeringBotanyInsect ConservationEntomologyPrecision Crop ProtectionDetection TechniqueForest EntomologyMultispectral AnalysisImage ClassificationImage AnalysisPattern RecognitionPublic HealthParasitologyMachine VisionWeed SeedsPest ManagementComputer VisionRecognition SuccessThermographyCrop ProtectionPest ControlSymbiosis
Digital imaging techniques were used to identify insects and body parts (adult lesser grain borer) ofRhyzopertha dominica beetles in bulk wheat samples. The samples contained dockage (weed seeds and damaged wheatkernels), which made the identification of insects more difficult. Multispectral analysis (Red, Green, Blue) was used incombination with pattern recognition techniques. Insect identification experiments were done with subimages of 8 8pixels. Statistical multivariate analysis and structural patterns were used for finding insects. The position of the insect(ventral, dorsal, side) and particles clinging to the insect affected recognition success. Recognition success of R.Dominica adults, some grass seeds, and other non-wheat components was higher than 90%.
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