Glass Defect Detection System Based on Deep Learning
Overview
Prof. LIU Ming of HKUST and his team developed an automatic mobile phone screen detection system, which includes a high-resolution glass imaging device and an algorithm for detecting defects based on deep learning.
Commercialisation opportunities
Technology licensing agreement
Problem addressed
The glass defect detection system enables real-time detection of glass defects of <10nm wide, which replaces the traditional detection means using human eyes, significantly enhancing productivity and accuracy of mobile phone production.
Innovation
- A high-resolution glass imaging device includes a customised lighting device, an automatic conveyor belt and a line scan camera. Through calculations and programming, the device can generate high-resolution images by locating the conveyor belt and combining line graphs
- A graph-based segmentation network based on deep learning enables real-time detection of the type of glass defect, such as scratch, hole, gap, etc.
Key impact
- The device can function for 24 hours continuously
Application
- Highly applicable such as phone screen production, printed circuit board production inspection, etc.
- High efficiency
- High expandability
The Hong Kong University of Science and Technology (HKUST)
The Hong Kong University of Science and Technology (HKUST) (https://hkust.edu.hk/) is a world-class research intensive university that focuses on science, technology and business as well as humanities and social science. HKUST offers an international campus, and a holistic and interdisciplinary pedagogy to nurture well-rounded graduates with global vision, a strong entrepreneurial spirit and innovative thinking. Over 80% of our research work were rated “Internationally excellent” or “world leading” in the Research Assessment Exercise 2020 of Hong Kong’s University Grants Committee. We were ranked 3rd in Times Higher Education’s Young University Rankings 2022, and our graduates were ranked 23rd worldwide and among the best from universities from Asia in Global University Employability Survey 2021.
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