Defect Detection of Printed Fabric Based on RGBAAM and Image Pyramid

Author:

Jing Junfeng1,Ren Huanhuan1

Affiliation:

1. School of Electronic Information , Xi’an Polytechnic University , Xi’an , Shaanxi , China

Abstract

Abstract To solve the problem of defect detection in printed fabrics caused by abundant colors and varied patterns, a defect detection method based on RGB accumulative average method (RGBAAM) and image pyramid matching is proposed. First, the minimum period of the printed fabric is calculated by the RGBAAM. Second, a Gaussian pyramid is constructed for the template image and the detected image by using the minimum period as a template. Third, the similarity measurement method is used to match the template image and the detected image. Finally, the position of the printed fabric defect is marked in the image to be detected by using the Laplacian pyramid restoration. The experimental results show that the method can accurately segment the printed fabric periodic unit and locate the defect position. The calculation cost is low for the method proposed in this article.

Publisher

Walter de Gruyter GmbH

Subject

General Materials Science

Reference16 articles.

1. Xin, J., Wu, J., Yao, P. P., Shao, S. (2018). An empirical study on fabric image retrieval with multispectral images using color and pattern features. In: Progress in Color Studies: Cognition, Language and Beyond, 391.

2. Zhang, H., Li, R., Jing, J., Li, P., Zhao, J. (2015). Fabric defect detection based on Frangi filter and fuzzy C-means algorithm in combination. Journal of Textile Research, 36(09), 120–124.

3. Zhang, Z.-F., Zhai, Y.-S., Guo, Y.-Y. et al. (2015). Research on method to measure cotton defects based on optoelectronics technique. Laser and Optoelectronics Progress, 52(3), 154–159.

4. Grigorescu, S.E., Petkov, J.M.F. (2003). Texture analysis using Renyi's generalized entropies. In: Proceedings 2003 International Conference on Image Processing. IEEE, 2003, 1, I–241.

5. Lin, J.J. (2002). Applying a co-occurrence matrix to automatic inspection of weaving density for woven fabrics. Textile Research Journal, 72(6), 486–490.

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