Defect Detection Based on Vision Sensors
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 12
Special Issue Editors
Interests: electromagnetic nondestructive testing
Interests: micronano dynamic testing and characterization
Special Issues, Collections and Topics in MDPI journals
Interests: visual inspection and characterization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the era of Industry 4.0 and smart manufacturing, ensuring product quality and operational safety is paramount. Automated defect detection has emerged as a critical technology across numerous industries, including manufacturing, aerospace, robotics, agriculture, and infrastructure monitoring. Traditional manual inspection methods are often slow, subjective, prone to human error, and unsuitable for high-volume production lines. The integration of advanced computer vision and a diverse array of sensors offers a powerful, non-destructive, and efficient solution to these challenges.
This Special Issue aims to gather the latest research and innovative applications that leverage the synergy of computer vision and multi-modal sensor data for automatic defect detection. We seek to explore how the fusion of visual data (2D/3D) with information from other sensors (e.g., thermal, hyperspectral, ultrasonic, LiDAR, IoT) can overcome the limitations of single-modality approaches. The goal is to create more robust, accurate, and intelligent systems capable of identifying anomalies, cracks, surface defects, and structural flaws in complex and demanding environments.
Dr. Pu Huang
Dr. Liuyong Chang
Dr. Xiangdong Ma
Guest Editors
Manuscript Submission Information
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Keywords
- nondestructive testing
- computer vision
- visual inspection and characterization
- robot vision
- multi-modal sensor
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