Gandhimathinathan A, A. B, Balaji R, D. T, Sabarisrinivas K R
{"title":"Using DLT for Textile Fabric Inspection: A Novel Network for Detecting Fabric Defects","authors":"Gandhimathinathan A, A. B, Balaji R, D. T, Sabarisrinivas K R","doi":"10.1109/ViTECoN58111.2023.10157629","DOIUrl":null,"url":null,"abstract":"This research paper proposes a novel network that uses Distributed Ledger Technology (DLT) for automated textile fabric inspection to detect fabric defects accurately and efficiently. The traditional method of visual inspection by human operators is subjective, time-consuming, and prone to errors, resulting in low productivity and increased cost. Automated inspection methods, such as machine vision and machine learning, can help improve the quality of textile products by providing a more objective and accurate inspection process. DLT can provide an additional layer of security and transparency to the fabric inspection process. Overall, the proposed system has the potential to improve the efficiency, accuracy, and reliability of the textile fabric inspection process.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ViTECoN58111.2023.10157629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This research paper proposes a novel network that uses Distributed Ledger Technology (DLT) for automated textile fabric inspection to detect fabric defects accurately and efficiently. The traditional method of visual inspection by human operators is subjective, time-consuming, and prone to errors, resulting in low productivity and increased cost. Automated inspection methods, such as machine vision and machine learning, can help improve the quality of textile products by providing a more objective and accurate inspection process. DLT can provide an additional layer of security and transparency to the fabric inspection process. Overall, the proposed system has the potential to improve the efficiency, accuracy, and reliability of the textile fabric inspection process.