Real-time curvature defect detection on outer surfaces using best-fit polynomial interpolation
Ehsan Golkar1, Anton Satria Prabuwono, Ahmed Patel
1Center for Artificial Intelligence Technology (CAIT), Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600 UKM Bangi, Selangor, Malaysia. egolkar@ftsm.ukm.my
This study introduces a new real-time defect detection system using best-fit polynomial interpolation for surface inspection. The method effectively identifies various surface defects like waviness, curvature, and blobs on pipes and tiles.
Area of Science:
- Materials Science
- Surface Metrology
- Computer Vision
Background:
- Surface inspection is critical for quality control in manufacturing.
- Existing methods may lack real-time capabilities or struggle with diverse defect types.
- Automated defect detection enhances efficiency and accuracy.
Purpose of the Study:
- To develop and validate a novel, real-time defect detection system for outer surfaces.
- To employ best-fit polynomial interpolation for enhanced feature extraction.
- To accurately identify flatness, waviness, blob, and curvature faults.
Main Methods:
- Implementation of a real-time defect detection system.
- Utilizing best-fit polynomial interpolation for feature extraction.
- Testing and validation on physical samples, including pipes and ceramic tiles.
Main Results:
- The system successfully recognizes physical defects, such as abnormal popped-up blobs.
- Flames, waviness, and curvature faults are detected simultaneously and accurately.
- The method demonstrates effectiveness in real-time surface condition inspection.
Conclusions:
- The proposed best-fit polynomial interpolation method offers a robust solution for real-time surface defect detection.
- This system enhances the capability to identify multiple surface defects concurrently.
- The validated results confirm the system's applicability in industrial quality control settings.
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