Transactions of the ASAE · 1992 · 32 citations · 0 references
ComputingComputer ScienceFood ScienceComputer VisionMachine VisionMeat InspectionAgricultural Machine VisionDefect ClassificationDefect DetectionFault DetectionFood InspectionObject RecognitionAutomated GradingAutomated Optical InspectionAutomatic Visual InspectionData Processing AlgorithmsImage Processing AlgorithmsImage-based GradingLinear Discriminant AnalysisVisual Inspection Systems
Mechanizing the harvest and grading of fresh market asparagus while maintaining quality presents a major challenge. Image processing algorithms were tested for detecting asparagus defects. Spreading tips were correctly identified with an 8% error rate, broken tips were detected with a 25% error rate, and scarred or cracked spears were detected with a 42% error rate using multivariate discriminant functions.