Journal ArticleDOI
Detecting Defects in Fabric with Laser-Based Morphological Image Processing
TLDR
In this paper, a spatial filter is placed at the Fourier plane to remove the periodic grating structure of the fabric from the image and morphological operations with a critically selected structuring element are then applied to the image after suitable pre-processing.Abstract:
Morphological operations such as erosion and opening are applied to both direct and spatially filtered images of test fabrics to identify defects. Detecting defects morpholog ically on spatially filtered images of fabrics produces better results, particularly when the fabric is fine and contains defects of small size. The diffraction pattern of the test fabric is obtained optically by illuminating it with a collimated laser beam. A spatial filter is placed at the Fourier plane to remove the periodic grating structure of the fabric from the image. Morphological operations with a critically selected structuring element are then applied to the image after suitable pre-processing.read more
Citations
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Journal ArticleDOI
Computer-Vision-Based Fabric Defect Detection: A Survey
TL;DR: This paper attempts to present the first survey on fabric defect detection techniques presented in about 160 references, and suggests that the combination of statistical, spectral and model-based approaches can give better results than any single approach.
Journal ArticleDOI
A Review of Recent Advances in Surface Defect Detection using Texture analysis Techniques
TL;DR: This paper systematically review recent advances in surface inspection using computer vision and image processing techniques, particularly those based on texture analysis methods, to review the state-of-the-art techniques for the purposes of visual inspection and decision making schemes that are able to discriminate the features extracted from normal and defective regions.
Journal ArticleDOI
A Generic Deep-Learning-Based Approach for Automated Surface Inspection
TL;DR: A generic approach that requires small training data for ASI is proposed, which builds classifier on the features of image patches, where the features are transferred from a pretrained deep learning network.
Journal ArticleDOI
An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces
Shuang Mei,Hua Yang,Zhouping Yin +2 more
TL;DR: This paper proposes an approach to detect and localize defects with only defect-free samples for model training by reconstructing image patches with convolutional denoising autoencoder networks at different Gaussian pyramid levels, and synthesizing detection results from these different resolution channels.
Journal ArticleDOI
Visual-Based Defect Detection and Classification Approaches for Industrial Applications-A SURVEY.
Tamas Czimmermann,Gastone Ciuti,Mario Milazzo,Marcello Chiurazzi,Stefano Roccella,Calogero Maria Oddo,Paolo Dario +6 more
TL;DR: This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles, and describes artificial visual processing techniques that are aimed at understanding of the captured scenery in a mathematical/logical way.
References
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Book
Image Analysis and Mathematical Morphology
TL;DR: This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
Book
Mathematical Morphology in Image Processing
TL;DR: This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.
Journal ArticleDOI
Fabric Defect Detection and Classification Using Image Analysis
TL;DR: In this paper, the authors used conventional image analysis hardware to image solid-shade, unpattemed, woven fabrics and two different software approaches for detecting and classifying knot and slub defects were studied.
Journal ArticleDOI
Identifying Fabric Structures with Fast Fourier Transform Techniques
TL;DR: A parallel version of the FFT for weaving has been developed that automates the very labor-intensive and therefore time-heavy and expensive process of hand-winding the fabric.
Journal ArticleDOI
Applying Fourier and Associated Transforms to Pattern Characterization in Textiles
TL;DR: The regular periodic nature of many textile patterns permits Fourier transform techniques in image processing to be used to measure their visual characteristics in carpets, the patterns may be due as mentioned in this paper, and the pattern may be found in many fabrics.