Applications of Artificial Intelligence in Computer Vision for the Identification of Fabric Faults in Textile Production

Fabric production faces major deficiencies in the identification of faults in traditional systems owing to human errors and a lack of verification. The conventional system identifies faults using manual examination techniques, which consume labor time and are work intensive to forecast quality production. To overcome these problems, there is a need for an automatic fabric fault detection system inspired by the latest technology, artificial intelligence. This study aims to design and implement a computerized fabric fault identification system to address these challenges using machine-learning algorithms. The development of intelligent systems increases the production of manufacturers with economic benefits. This study presents efficiency and quality control parameters for improving the textile sector. The proposed system considers a fault identification system using pictures and videos. Further innovation in this technology improves the commercial application of initial fabric fault detection.