Fringe pattern defect identification using Kalman filter and machine learning

Dhruvam Pandey; Rajshekhar Gannavarpu; Rajshekhar Gannavarpu

doi:10.1364/DH.2022.W2A.6

Digital Holography and 3-D Imaging 2022
Technical Digest Series (Optica Publishing Group, 2022),
paper W2A.6
•https://doi.org/10.1364/DH.2022.W2A.6

Fringe pattern defect identification using Kalman filter and machine learning

Dhruvam Pandey and Rajshekhar Gannavarpu

Digital Holography and Three-Dimensional Imaging 2022

Cambridge United Kingdom
1–4 August 2022
ISBN: 978-1-957171-12-8

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D. Pandey and R. Gannavarpu, "Fringe pattern defect identification using Kalman filter and machine learning," in Digital Holography and 3-D Imaging 2022, D. Chu, J. Park, C. Cheng, and P. Ferraro, eds., Technical Digest Series (Optica Publishing Group, 2022), paper W2A.6.

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Abstract

The article introduces a Kalman filter and naive Bayes classifier based machine learning model for defect identification in the noisy fringe pattern. The simulation results corroborate the performance of the proposed method.

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