Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013 · 31 citations · 0 references
ComputingComputer ScienceCrop SciencesComputer VisionDigital ImagingMachine LearningClassificationImage AnalysisImage ClassificationPattern RecognitionPest DetectionPest IdentificationDigitization Of PhotographsGraphical ModelsImage Classification For CropsImage-based Insect IdentificationImage-based Pest DetectionImage-based Pest RecognitionMachine Vision For OrchardsNeural Network Classification
The aim of this work was a neural identification of selected apple tree orchard pests. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning sets acquired on the basis of information contained in digital photographs of pests. In particular, the problem of identifying 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the agrofags, neural modelling methods were utilized, supported by digital analysis of image techniques.