Defect Detection of Printed Fabric Based on RGBAAM and Image Pyramid

• Autorzy: Jing, Junfeng , Ren, Huanhuan
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

PL

RGBAAM; piramida Gaussa; segmentacja; wykrywanie defektów

EN

RGBAAM; Gaussian pyramid; periodic segmentation; defect detection

• Czasopismo: Autex Research Journal
• Rocznik: 2021
• Tom: Vol. 21, no. 2
• Strony: 135--141
• Opis fizyczny: Bibliogr 16 poz.

Twórcy

autor

Jing, Junfeng

• School of Electronic Information, Xi’an Polytechnic University, Xi’an, Shaanxi 710048, China,

autor

Ren, Huanhuan

• School of Electronic Information, Xi’an Polytechnic University, Xi’an, Shaanxi 710048, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).

Identyfikatory

DOI

10.2478/aut-2020-0007