MATLAB-Based Glove Defect Detection System

MATLAB | Image Processing | Computer Vision

Developed a Glove Defect Detection (GDD) system using MATLAB, designed to enhance quality control in glove manufacturing. The system applies advanced image processing techniques to detect defects in disposable, cotton, and leather gloves, ensuring compliance with high-quality standards in industries such as healthcare and food processing.

Processing Workflow

1. Low-Level Processing: Involves grayscale conversion, Gaussian filtering, contrast stretching, and sharpening to improve image quality and reduce noise.

2. Mid-Level Processing Employs threshold and edge segmentation, with the Canny edge detector offering high accuracy for identifying defects.

3. High-Level Processing Utilizes part extraction and K-means clustering for glove color analysis, along with Delta E color difference calculations to detect defects.

Key Features

• Image preprocessing and enhancement techniques
• Advanced segmentation methods for defect identification
• Color-based defect detection using Delta E and K-means clustering
• User-friendly graphical interface for glove image analysis