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Automated inspection system now a day is a must in mass production lines. To optimize the abilities of the inspection system using computer vision (CV) technology in terms of accuracy and speed the input data should be as good as possible. The quality of input data for a computer vision system plays a very important role in this story. We can define a high-quality image as one that is characterized by clarity, sharp contrast, exceptional resolution, and a high system resolution (um/pixel). The ability to highlight defects in contrast to non-defective areas within a sample is a critical aspect of good input data, as it facilitates precise defect detection. When input data meets these criteria, computer vision systems can operate with enhanced accuracy and speed, ultimately improving the overall efficiency of quality control processes. All above requirements can be archived just in case considering to the optical system (OPS) of CS system. The design of an optical system will be based on samples as per material, dimension, defect descriptions and requested system speed. There's many types of inspected samples and defects that will lead to the OPS's design being impossible or cannot be optimized to fit with requested requirement. One of them is the thin and transparent surface with tiny defects as: crack, dent, chip off... with the size of couple of 100 µm. This paper introduces an OPS specifically tailored for inspecting storage disk surfaces before the coating stage in production lines, addressing these challenges. The goal is to enhance precision and efficiency in defect detection, contributing to advancements in automated inspection systems for specialized industrial applications.

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Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Dau, S. H., Ta, H., Le, K., & Dang, T. P. (2023). Optical System for Thin Transparent Surface Inspection. VNUHCM Journal of Engineering and Technology, 5(SI2), 1-9.

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