Defect localization in noisy fringe patterns using subspace method and naive Bayes classifier

Jagadesh Ramaiah; Rajshekhar Gannavarpu

doi:10.1364/AIS.2021.JTh6A.31

OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES)
OSA Technical Digest (Optica Publishing Group, 2021),
paper JTh6A.31
•https://doi.org/10.1364/AIS.2021.JTh6A.31

Defect localization in noisy fringe patterns using subspace method and naive Bayes classifier

Jagadesh Ramaiah and Rajshekhar Gannavarpu

Applied Industrial Spectroscopy 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-90-3

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Joint Poster Session III (JTh6A)

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J. Ramaiah and R. Gannavarpu, "Defect localization in noisy fringe patterns using subspace method and naive Bayes classifier," in OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES), S. Buckley, F. Vanier, S. Shi, K. Walker, I. Coddington, S. Paine, K. Lok Chan, W. Moses, S. Qian, P. Pellegrino, F. Vollmer, G. , J. Jágerská, R. Menzies, L. Emmenegger, and J. Westberg, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper JTh6A.31.

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Abstract

Here, we present an effective defect identification method using phase deriva- tives as feature vectors and a naive Bayes classifier to predict defective pixels. Simulation results are shown to illustrate the performance of the proposed method.

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