A Public Fabric Database for Defect Detection Methods and Results
Author:
Affiliation:
1. ITI, DISCA , Universitat Politècnica de València, UPV , València , Spain
2. AITEX , Plaza Emilio Sala, 1, 03801 Alcoy , Spain
Abstract
Publisher
Walter de Gruyter GmbH
Subject
General Materials Science
Link
https://www.sciendo.com/pdf/10.2478/aut-2019-0035
Reference75 articles.
1. [1] Kumar, A. (2008). Computer-vision-based fabric defect detection: a survey. IEEE Transactions on Industrial Electronics, 55(1), 348-363.10.1109/TIE.1930.896476
2. [2] Ngan, H. Y., Pang, G. K., Yung, N. H. (2011). Automated fabric defect detection – a review. Image and Vision Computing, 29(7), 442-458.10.1016/j.imavis.2011.02.002
3. [3] Habib, T., Faisal, R., Rokonuzzaman, M., Ahmed, F. (2014). Automated fabric defect inspection: a survey of classifiers. International Journal in Foundations of Computer Science & Technology (IJFCST), 4(1), 17-25.10.5121/ijfcst.2014.4102
4. [4] Hanbay, K., Talu, M., Özguven, Ö. (2016). Fabric defect detection systems and methods. A systematic literature review. Optik, 127, 11960-11973.10.1016/j.ijleo.2016.09.110
5. [5] Goyal, A. (2018). Automation in fabric inspection, in Automation in Garment Manufacturing, Woodhead Publishing, 75-107.10.1016/B978-0-08-101211-6.00004-5
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