Artificial Vision Systems for Industrial and Textile Control
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".
Deadline for manuscript submissions: closed (10 June 2023) | Viewed by 7065
Special Issue Editors
Interests: textile engineering; machine vision; artificial neural networks; spectrophotometry; colorimetry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue features articles related to Sustainable Industry with particular reference to the development of advanced systems based on 2D and 3D Artificial Vision for industrial and textile control. In the manufacturing sector, and even more in the textile industry, inspection of products is a crucial task to improve the quality and to reduce the cost. Human-based inspection is inefficient due to high labour intensity and it often leads to unreliable and unrepeatable results.
Artificial Vision (AV) proved to be effective in overcoming human-based inspection by both using 2D Machine Vision and by developing 3D-based acquisition. Using such systems, it is possible to provide defect detection, classification, measurements and quali-quantitative certification of inspected products quality. This is even more true in recent years where we have witnessed an increasing development of 2D and 3D acquisition methods that can impair the quality of inspection.
In this context, the present Special Issue aims to promote papers related to Artificial Vision findings and applications in all industrial fields, with a particular focus on the textile industry. Contributed papers can vary from basic science to practical methods and from new developments to future perspectives. Hybrid techniques that combine the integration of AV with Artificial Intelligence are encouraged.
In the Special Issue, we want to address, in particular, but not exclusively, recent advances in the following topics:
- 2D Machine Vision (using industrial cameras, line scan scameras, optical fibers, spectrophotometers, etc.);
- 3D Machine Vision (using 3D scanners, RGB-D devices, etc.);
- Artificial Intelligence-based methods for the detection, classification and characterization of industrial products;
- Methods and systems for the real-time detection of defects;
- Colorimetry and spectrophotometry;
- Image-processing based algorithms;
- Performance critera for the assessment of the reliability of AV systems;
- New architectures for 2D and 3D AV;
- Human–machine interaction for quality control;
- Big data and data analytics for textile and industrial defects classification;
- Machine integration of inspection systems;
- New hardware for machine vision;
- Robotics for product inspection.
Prof. Dr. Rocco Furferi
Dr. Michaela Servi
Guest Editors
Manuscript Submission Information
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Keywords
- 2D machine vision
- 3D machine vision
- reverse engineering
- spectrophotometry
- colorimetry
- textiles
- fabrics
- yarns
- fibers
- quality assessment
- cameras
- smart cameras
- defect detection
- real-time imaging
- image processing
- human-machine interaction
- defects classification
- defect taxonomy
- defect detection
- 3D scanner
- big data analytics
- neural networks
- deep learning
- artificial intelligence
- deterministic methods
- imaging software
- imaging hardware
- robotics for imaging
- product inspection
- machine integration
- illumination systems
- infrared imaging
- UV-based imaging
- automated inspection
- optics
- lasers
- image segmentation
- image recognition
- pattern recognition
- metrological assessment
- thermography
