Computer Vision on X-Ray Data in Industrial Production and Security Applications : A Comprehensive Survey
Abstract
X-ray imaging technology has been used for decades in clinical tasks to reveal the internal condition of different organs, and in recent years, it has become more common in other areas such as industry, security, and geography. The recent development of computer vision and machine learning techniques has also made it easier to automatically process X-ray images and several machine learning-based object (anomaly) detection, classification, and segmentation methods have been recently employed in X-ray image analysis. Due to the high potential of deep learning in related image processing applications, it has been used in most of the studies. This survey reviews the recent research on using computer vision and machine learning for X-ray analysis in industrial production and security applications and covers the applications, techniques, evaluation metrics, datasets, and performance comparison of those techniques on publicly available datasets. We also highlight some drawbacks in the published research and give recommendations for future research in computer vision-based X-ray analysis.
Main Authors
Format
Articles
Research article
Published
2023
Series
Subjects
Publication in research information system
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202301131304Käytä tätä linkitykseen.
Review status
Peer reviewed
ISSN
2169-3536
DOI
https://doi.org/10.1109/access.2023.3234187
Keywords
computer visiondeep learningX-rayindustrial applicationssecurity applicationskonenäkösyväoppiminenröntgensäteily
Language
English
Published in
IEEE Access
Citation
- Rafiei, M., Raitoharju, J., & Iosifidis, A. (2023). Computer Vision on X-Ray Data in Industrial Production and Security Applications : A Comprehensive Survey. IEEE Access, 11, 2445-2477. https://doi.org/10.1109/access.2023.3234187
Copyright© Authors, 2023