Automatic Printed Fabric Defect Detection Using A Convolutional Neural Network
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Automatic Printed Fabric Defect Detection Using A Convolutional Neural Network
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Author : Samit Chakraborty
language : en
Publisher:
Release Date : 2021
Automatic Printed Fabric Defect Detection Using A Convolutional Neural Network written by Samit Chakraborty and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Artificial Intelligence On Fashion And Textiles
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Author : Wai Keung Wong
language : en
Publisher: Springer
Release Date : 2018-10-13
Artificial Intelligence On Fashion And Textiles written by Wai Keung Wong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-13 with Technology & Engineering categories.
The book includes the Proceedings of the Artificial Intelligence on Fashion and Textiles conference 2018 which provides state-of-the-art techniques and applications of AI in the fashion and textile industries. It is essential reading for scientists, researchers and R&D professionals working in the field of AI with applications in the fashion and textile industry; managers in the fashion and textile enterprises; and anyone with an interest in the applications of AI. Over the last two decades, with the great advancement of computer technology, academic research in artificial intelligence (AI) and its applications in fashion and textile supply chain has been becoming a very hot topic and has received greater attention from both academics and industrialists. A number of AI-related techniques has been successfully employed and proven to handle the problems including fashion sales forecasting, supply chain optimization, planning and scheduling, textile material defect detection, fashion and textile image recognition, fashion image and style retrieval, human body modeling and fitting, etc.
On Loom Fabric Defect Inspection Using Contact Image Sensors And Activation Layer Embedded Convolutional Neural Network
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Author : Wenbin Ouyang
language : en
Publisher:
Release Date : 2018
On Loom Fabric Defect Inspection Using Contact Image Sensors And Activation Layer Embedded Convolutional Neural Network written by Wenbin Ouyang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Image converters categories.
Malfunctions on loom machines are the main causes of faulty fabric production. An on-loom fabric inspection system is a real-time monitoring device that enables immediate defect detection for human intervention. This dissertation presented a solution for the on-loom fabric defect inspection, including the new hardware design-the configurable contact image sensor (CIS) module-for on-loom fabric scanning and the defect detection algorithms. The main contributions of this work include (1) creating a configurable CIS module adaptable to a loom width, which brings CIS unique features, such as sub-millimeter resolution, compact size, short working distance and low cost, to the fabric defect inspection system, (2) designing a two-level hardware architecture that can be efficiently deployed in a weaving factory with hundreds of looms, (3) developing a two-level inspecting scheme, with which the initial defect screening is performed on the Raspberry Pi and the intensive defect verification is processed on the cloud server, (4) introducing the novel pairwise-potential activation layer to a convolutional neural network that leads to high accuracies of defect segmentation on fabrics with fine and imbalanced structures, (5) achieving a real-time defect detection that allows a possible defect to be examined multiple times, and (6) implementing a new color segmentation technique suitable for processing multi-color fabric defects. The novel CIS-based on-loom scanning system offered real-time and high-resolution fabric images, which was able to deliver the information of single thread on a fabric. The algorithm evaluation on the fabric defect datasets showed a non-miss-detection rate on defect-free fabrics. The average precision of defect existed images reached above 90% at the pixel level. The detected defect pixels' integrity-the recall scored around 70%. Possible defect regions overestimated on ground truth images and the morphologies of fine defects similar to regular fabric pattern were the two major reasons that caused the imperfection in defect pixel locating. The experiments showed the defect areas on multi-color fabrics could be precisely located under the proposed color segmentation algorithm.
Fabric Defect Detection By Wav
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Author : Tin-Chi Lee
language : en
Publisher: Open Dissertation Press
Release Date : 2017-01-27
Fabric Defect Detection By Wav written by Tin-Chi Lee and has been published by Open Dissertation Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Technology & Engineering categories.
This dissertation, "Fabric Defect Detection by Wavelet Transform and Neural Network" by Tin-chi, Lee, 李天賜, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled Submitted by LEE Tin Chi for the degree of Master of Philosophy at The University of Hong Kong in July 2004 Textile inspection plays an important role in maintaining the quality of products. In this thesis, three methods which utilize matched masks, wavelet transform and neural network are proposed for fabric defect detection. An evaluation of the performance of the methods was conducted on eight classes of fabric defects (Broken End, Dirty Yarn, Mispick, Netting Multiples, Slack End, Thick Bar, Thin Bar, and Wrong Draw). In the first method, a multi-channel filtering bank equipped with five matched masks was used. Matched masks are 2-D filters that characterize specific texture properties. They are designed to emphasize the Wrong Draw texture, the Mispick texture, the horizontal edges, the bars structure and the filled regions on fabric images. At the filter outputs, segmentation by thresholds is applied, followed by a logical OR operation. The total number of pixels exceeding the threshold on the resulting image determines whether the fabric image is defective or defect-free. Using this method, 96% of fabric defects were successfully detected, and the false alarm rate was 6%. The method achieved a 90% - 100% detection rate for most fabric defects, though the detection rate for Thin Bar defects was only 75%. The second method employed wavelet transform to decompose fabric images into multi-scales and orientations. During the training stage, the parameters to be optimized include the rotation angles and the two thresholds applied on the horizontal and vertical transformed images. The variation in rotation angles determines the selection of wavelet bases. During the detection stage, the discrimination criterion is based on the total number of defect windows. Using this method, only 76% of fabric defects were identified, and the false alarm rate was 7%. The detection rate for Dirty Yarn was high, but much lower for Broken End and Wrong Draw defects. The last method took advantage of the fault tolerance and learning ability of neural networks. We explored the texture structure of defect-free images so that feature extraction was conducted on repeating units with proper selection of locations. For defect images, similar feature vectors were extracted and passed to the neural network. Using this method, the detection rate was as high as 92% and the false alarm rate was 6%. Dirty Yarn, Netting Multiples, Mispick, Thin Bar and Wrong Draw defects were completely identified, while 75% of Broken End and Slack End defects were detected. However, only 73% of Thin Bar defects were detected. The method employing matched masks proved the most effective in detecting fabric defects. The neural network method was next best. The wavelet transform method was the least effective, because it was only able to detect effectively certain classes of fabric defects. Dirty Yarn, Netting Multiples, Mispick and Slack End defects are relatively easy to identify correctly. Wrong Draw and Thin Bar defects are less easy to detect and Broken End and Thick Bar defects are the most difficult to detect. DOI: 10.5353/th_b2928728 Subjects: Wavelets (Mathematics) Neural networks (Computer science) Textile fabrics - Testing
Advances In Simulation And Digital Human Modeling
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Author : Julia L. Wright
language : en
Publisher: Springer Nature
Release Date : 2021-06-26
Advances In Simulation And Digital Human Modeling written by Julia L. Wright and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-26 with Technology & Engineering categories.
This book provides readers with a timely snapshot of modeling and simulation tools, including virtual and mixed-reality environment, for human factors research. It covers applications in healthcare and physical ergonomics, military and transportation systems, industrial monitoring, as well as economics and social sciences. Based on the AHFE 2021 International Conference on Human Factors and Simulation and the AHFE 2021 International Conference on Digital Human Modeling and Applied Optimization, held virtually on 25–29 July, 2021, from USA, the book offers a unique resource for modelling and simulation researchers seeking insights into human factors research and to human factors experts seeking reliable computational tools.
2021 27th International Conference On Mechatronics And Machine Vision In Practice M2vip
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2021-11-26
2021 27th International Conference On Mechatronics And Machine Vision In Practice M2vip written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-26 with categories.
With the advent of new functional materials, smart actuators, smart sensors, embedded computers and 3D printing technologies, as well as the latest advance in machine vision, intelligence, machine learning and computational modeling, a lot of more intelligent, powerful, miniaturized or user friendly devices, systems and robots are emerging that meet the needs of modern day living The M2VIP 2020 aims to provide an international and interdisciplinary forum for the mechatronics and machine vision research community to explore the frontier of science and technology in smart actuators, smart sensors, intelligent machines, advanced robots, machine learning and artificial intelligence systems
Fabric Defect Detection By Wavelet Transform And Neural Network
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Author : Tin-chi Lee
language : en
Publisher:
Release Date : 2004
Fabric Defect Detection By Wavelet Transform And Neural Network written by Tin-chi Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Neural networks (Computer science) categories.
Proceedings Of Second International Conference On Advances In Computer Engineering And Communication Systems
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Author : A. Brahmananda Reddy
language : en
Publisher: Springer Nature
Release Date : 2022-02-22
Proceedings Of Second International Conference On Advances In Computer Engineering And Communication Systems written by A. Brahmananda Reddy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-22 with Technology & Engineering categories.
This book includes original, peer-reviewed research articles from International Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2021), held in VNR Vignana Jyoythi Institute of Engineering and Technology (VNR VJIET), Hyderabad, Telangana, India, during 13–14 August 2021. The book focuses on “Smart Innovations in Mezzanine Technologies, Data Analytics, Networks and Communication Systems” enlargements and reviews on the advanced topics in artificial intelligence, machine learning, data mining and big data computing, knowledge engineering, semantic Web, cloud computing, Internet on Things, cybersecurity, communication systems, and distributed computing and smart systems.
Eighth International Conference On Digital Image Processing Icdip 2016
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Author : Charles M. Falco
language : en
Publisher:
Release Date : 2016-10-30
Eighth International Conference On Digital Image Processing Icdip 2016 written by Charles M. Falco and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-30 with categories.
Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.
Artificial Intelligence And Soft Computing
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Author : Leszek Rutkowski
language : en
Publisher: Springer Nature
Release Date : 2021-10-04
Artificial Intelligence And Soft Computing written by Leszek Rutkowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-04 with Computers categories.
The two-volume set LNAI 12854 and 12855 constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2021, held in Zakopane, Poland, in June 2021. Due to COVID 19, the conference was held virtually. The 89 full papers presented were carefully reviewed and selected from 195 submissions. The papers included both traditional artificial intelligence methods and soft computing techniques as well as follows: · Neural Networks and Their Applications · Fuzzy Systems and Their Applications · Evolutionary Algorithms and Their Applications · Artificial Intelligence in Modeling and Simulation · Computer Vision, Image and Speech Analysis · Data Mining · Various Problems of Artificial Intelligence · Bioinformatics, Biometrics and Medical Applications