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arXiv Computer Vision By Ray Wai Man Kong, Ding Ning, Theodore Ho Tin Kong

AI Visual Inspection for Garment Production

Read the original on arXiv Computer Vision →

The paper introduces an AI-based visual inspection system for garment sewing-line quality control, employing Convolutional Neural Networks to detect defects such as broken and skipped stitches. The system was trained on black fabric and thread, and tested on various colors, successfully detecting jump defects on black, red, and dark green fabrics but showing limitations on broken defects and fabrics with markedly different visual characteristics. The study highlights that model accuracy depends heavily on training data diversity and the system’s ability to generalize across different fabric and thread colors.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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