Transactions of the ASAE · 1985 · 56 citations · 0 references
AgricultureFood ScienceHorticultural SciencesComputer VisionFruit ScienceMachine VisionAgricultural Machine VisionAutomated SortingFruit QualityFruit Quality EvaluationFruit SortingObject RecognitionAutomated GradingComputer Vision InspectionComputer Vision-based SortingImage-based GradingMachine Vision-based SortingQuality GradingVegetable SortingVisual Inspection Systems
ABSTRACT Amachine vision based inspection scheme has been developed for tomatoes which involves the analysis of stem and blossom end views for features indicative of fresh market quality. Suitable illumination and orientation techniques were designed. Evaluation of the complete tomato sorting system showed an error rate of 3.5%. Further studies demonstrated the flexibility of this package in implementing various grading schemes according to the needs of the marketplace. The feasibility of obtaining the sorting speeds required for commercial application was explored.