TY  - EJOU
AU  - Lee, Seungmin 
AU  - Kim, Beomseong 
AU  - Lee, Heesung 

TI  - Deep Learning-Based Glass Detection for Smart Glass Manufacturing Processes
T2  - Computers, Materials \& Continua

PY  - 2025
VL  - 84
IS  - 1
SN  - 1546-2226

AB  - This study proposes an advanced vision-based technology for detecting glass products and identifying defects in a smart glass factory production environment. Leveraging artificial intelligence (AI) and computer vision, the research aims to automate glass detection processes and maximize production efficiency. The primary focus is on developing a precise glass detection and quality management system tailored to smart manufacturing environments. The proposed system utilizes the various YOLO (You Only Look Once) models for glass detection, comparing their performance to identify the most effective architecture. Input images are preprocessed using a Gaussian Mixture Model (GMM) to remove background noise present in factory environments. This approach minimizes distractions caused by varying backgrounds and enables accurate glass identification and defect detection. Traditional manual inspection methods often require skilled labor, are time-intensive, and may lack consistency. In contrast, the proposed vision-based system ensures high accuracy and reliability through non-contact inspection. The performance of the system was evaluated using video data collected from an actual glass factory. This assessment verified the accuracy, reliability, and practicality of the system, demonstrating its effectiveness in real-world production scenarios. Beyond automating glass detection and defect identification, the proposed system integrates into manufacturing environments to support data-driven decision-making. This enables real-time monitoring, defect prediction, and improved production efficiency. Moreover, this research is expected to serve as a model for enhancing quality control and productivity across various manufacturing industries, driving innovation in smart manufacturing.
KW  - Object detection; glass detection; artificial intelligence (AI); smart manufacturing; quality management

DO  - 10.32604/cmc.2025.066152