Nonwoven fabric crease defects detection based on Gabor filter

Shaoqing Han; Feifei Gu

doi:10.1117/12.2525959

21 June 2019 Nonwoven fabric crease defects detection based on Gabor filter

Shaoqing Han, Feifei Gu

Proceedings Volume 11061, Automated Visual Inspection and Machine Vision III; 110610H (2019) https://doi.org/10.1117/12.2525959
Event: SPIE Optical Metrology, 2019, Munich, Germany

Abstract

The defect detection of nonwoven fabrics is one of the most important steps of fabric quality assurance on production lines. For a long time, fabric defects detection has been carried out manually by human vision with an accuracy of about 60–70%, which not only affects the health of the inspectors, but also has high inspection cost. How to automatically detect crease defects of various forms at a high accuracy has been a challenging task in the field of machine vision. At present, Fourier transform and wavelet transform have been adopted to solve this problem. However, both of them can hardly detect stochastic textured in local region from different scales and directions. This paper adopted a 2D Gabor filter-based method to detect the crease defects, which has tunable angular and axial frequency bandwidth, tunable center frequencies, and could achieve optimal joint resolution in spatial and frequency domain. Firstly the fabric crease images are transformed from the spatial domain to the frequency domain. Secondly the frequency domain images are filtered by the Gabor filter with adjustable central frequency, bandwidth and azimuth, and the frequency domain images of the crease pattern are selected in the frequency domain image. Then they are reversed to the spatial domain. Finally the crease area of nonwoven fabric is obtained by the blob analysis. Experiments conducted on various forms of crease defects have shown that by adopting the proposed method, the nonwoven fabric’s crease defects can be detected effectively and accurately.

Citation Download Citation

Shaoqing Han and Feifei Gu "Nonwoven fabric crease defects detection based on Gabor filter", Proc. SPIE 11061, Automated Visual Inspection and Machine Vision III, 110610H (21 June 2019); https://doi.org/10.1117/12.2525959

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available