Detection and Classification of Faulty Weft Threads Using Both Feature-Based and Deep Convolutional Machine Learning Methods
Kopaczka M, Saggiomo M, Güttler M, Kielholz K, Merhof D (2019)
Publication Type: Conference contribution
Publication year: 2019
Journal
Publisher: Springer Verlag
Book Volume: 11351 LNCS
Pages Range: 141-163
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Funchal, PRT
ISBN: 9783030054984
DOI: 10.1007/978-3-030-05499-1_8
Abstract
In our work, we analyze how faulty weft threads in air-jet weaving machines can be detected using image processing methods. To this end, we design and construct a multi-camera array for automated acquisition of images of relevant machine areas. These images are subsequently fed into a multi-stage image processing pipeline that allows defect detection using a set of different preprocessing and classification methods. Classification is performed using both image descriptors combined with feature-based machine learning algorithms and deep learning techniques implementing fully convolutional neural networks. To analyze the capabilities of our solution, system performance is thoroughly evaluated under realistic production settings. We show that both approaches show excellent detection rates and that by utilizing semantic segmentation acquired from a fully convolutional network we are not only able to detect defects reliably but also classify defects into different subtypes, allowing more refined strategies for defect removal.
Involved external institutions
Germany (DE)How to cite
APA:
Kopaczka, M., Saggiomo, M., Güttler, M., Kielholz, K., & Merhof, D. (2019). Detection and Classification of Faulty Weft Threads Using Both Feature-Based and Deep Convolutional Machine Learning Methods. In Gabriella Sanniti di Baja, Ana Fred, Maria De Marsico (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 141-163). Funchal, PRT: Springer Verlag.
MLA:
Kopaczka, Marcin, et al. "Detection and Classification of Faulty Weft Threads Using Both Feature-Based and Deep Convolutional Machine Learning Methods." Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018, Funchal, PRT Ed. Gabriella Sanniti di Baja, Ana Fred, Maria De Marsico, Springer Verlag, 2019. 141-163.
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