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This document describes the development of a low-cost machine vision system using webcams and image processing algorithms to detect defects and sort tomatoes. Two major tomato defects - Blossom End Rot (BER) and cracks - can be identified and separated from good tomatoes using color and shape features extracted via the algorithms. The system achieves an inspection speed of 180 tomatoes per minute with 84-87.5% accuracy of defect detection using either rule-based or neural network-based classification approa

Author

Phạm Quang

Language

EN