Vision-Inspection-Synchronized Dual Optical Coherence Tomography for High-Resolution Real-Time Multidimensional Defect Tracking in Optical Thin Film Industry
Deokmin Jeon,
Unsang Jung,
Kibeom Park,
Pilun Kim,
Sangyeob Han,
Hyosang Jeong,
Ruchire Eranga Wijesinghe,
Naresh Kumar Ravichandran,
Jaeyul Lee,
Youngmin Han,
Mansik Jeon,
Jeehyun Kim
Affiliations
Deokmin Jeon
School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, South Korea
Unsang Jung
ICT Convergence Research Division, Digital Healthcare Research Center, Gumi Electronics and Information Technology Research Institute (GERI), Gumi, South Korea
Kibeom Park
Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
Pilun Kim
Institute of Biomedical Engineering Research, Kyungpook National University, Daegu, South Korea
Sangyeob Han
School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, South Korea
Hyosang Jeong
School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, South Korea
Ruchire Eranga Wijesinghe
Department of Biomedical Engineering, College of Engineering, Kyungil University, Gyeongsan, South Korea
Large-scale product inspection is an important aspect in thin film industry to identify defects with a high precision. Although vision line scan camera (VLSC)-based inspection has been frequently implemented, it is limited to surface inspections. Therefore, to overcome the conventional drawbacks, there is a need to extend inspection capabilities to internal structures. Considering that VLSC systems have access to rich information, such as color and texture, high-resolution real-time multimodal optical synchronization between VLSC and dual spectral domain optical coherence tomography (SD-OCT) systems was developed with a laboratory customized in-built automated defect-tracking algorithm for optical thin films (OTFs). Distinguishable differences in the color and texture of the bezel area were precisely determined by the VLSC. Detailed OCT assessments were conducted to verify the detection of previously unobtainable border regions and micrometer-range sub-surface defects. To enhance the accuracy of the method, VLSC images were aided for the precise surface defect identification using OCT and the image acquisition, signal processing, image analysis, and classification of both techniques were simultaneously processed in real-time for industrial applicability. The results demonstrate that the proposed method is capable of detecting and enumerating total number of defects in OTF samples with exceptional resolution and in a cost-effective manner facilitating wide area inspection for OTF samples.
