Project
Machine Learning
Durian Defect and Grading System Using Computer Vision
Computer-vision inspection system that detects cracks, insect damage, and fungal infection to sort durian fruit into Premium, Grade A, and Grade B tiers.
Project Overview
An agricultural quality-control system using Python and OpenCV to inspect durian fruit surfaces for cracks, insect damage, and fungal infection.
Classifies each fruit into standardized quality grades (Premium, Grade A, Grade B) to replace subjective manual sorting with consistent, repeatable grading.
Key Highlights
- Automated surface defect detection for cracks, pests, and fungal blemishes.
- Objective multi-tier grading (Premium, Grade A, Grade B) using computer vision.
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