Hoon Kiang Tan
Papers
1
Total Citations
8
H-Index
1
About
Dr. Hoon Kiang Tan is a researcher specializing in automated visual inspection and defect detection for industrial robotics applications. His work focuses on developing computer vision frameworks that enable robots to identify surface anomalies on metal components, particularly blistering defects. In his most cited work (2017, 8 citations), Dr. Tan proposed a novel detection framework that converts input images into Histogram of Oriented Gradient (HOG) representations to capture critical contour information, then performs nearest-neighbor searches against a defect database. This approach bridges the gap between traditional manual inspection and fully automated robotic quality control systems. While his citation count reflects the specialized nature of his research area, his contributions are significant for advancing autonomous inspection in manufacturing environments. Dr. Tan's work demonstrates the practical application of machine vision techniques to real-world industrial challenges, offering a foundation for future developments in robotic surface inspection and quality assurance.
Research Focus
Key Achievements
Top Papers
- 1