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16 October 2019 A GPU assisted space frequency method for dynamic defect detection in optical metrology
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Proceedings Volume 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019); 1120526 (2019) https://doi.org/10.1117/12.2541658
Event: Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 2019, Phuket, Thailand
Abstract
The study of defect dynamics is an important problem in the field of non-destructive testing, crack propagation and fracture mechanics. Optical interferometric techniques are extensively used for this purpose because of their non-invasive behaviour and full field operation. The fringe patterns obtained from these techniques serve as good indicators for finding defects. In dynamic defect analysis, a large number of fringe patterns are captured and processed. The regions where the fringe density varies significantly are classified as defects. Thus, a fast, reliable and robust algorithm for identifying the rapid variations of fringe density is required. In this paper, we propose a graphics processing unit (GPU) assisted space frequency method based on windowed Fourier spectrum analysis for processing the dynamically varying fringe patterns. The main advantage of this approach is high computational efficiency achieved using GPU computing framework. The performance of the proposed method is demonstrated using 100 simulated fringe patterns, each of size 2048 x 2048 pixels. This large data stack was efficiently processed using the proposed method within only a minute, and thus, the proposed method offers the feasibility of high speed defect analysis. The practical application of the proposed method is explored by processing the fringe patterns obtained from the propagation of micron sized defects in an experimental configuration based on common-path diffraction phase microscopy setup.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sreeprasad Ajithaprasad, Vigneshwar Rajendran, and Rajshekhar Gannavarpu "A GPU assisted space frequency method for dynamic defect detection in optical metrology", Proc. SPIE 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 1120526 (16 October 2019); https://doi.org/10.1117/12.2541658
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