Phase Extraction of Electronic Speckle Interference Fringe Image based on Convolutional Neural Network
Authors: 
Fang Zhang, Rui Zhao, Wen Wang, Yang LiuAuthors Info & Claims
Fang Zhang, Rui Zhao, Wen Wang, Yang LiuAuthors Info & ClaimsPages 138 - 145
Abstract
Electronic speckle pattern interferometry (ESPI) is a kind of full-field, non-contact nondestructive measurement technology, which is suitable for deformation measurement and nondestructive testing of optical rough surface. Fringe phase is an important information of interference fringe image, and the accuracy of phase estimation plays an important role in the extraction of fringe information. However, because of the discontinuity of fringe image and the influence of noise, phase extraction has always been a challenging problem. In this paper, we propose a fringe image phase extraction technique based on convolutional neural network, and experimental results show that this method has a good effect on phase estimation of the interference fringe.
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Published In
April 2021
498 pages
ISBN:9781450389501
DOI:10.1145/3467707
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Published: 24 September 2021
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- Program for Innovative Research Team in University of Tianjin
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ICCAI '21
ICCAI '21: 2021 7th International Conference on Computing and Artificial Intelligence
April 23 - 26, 2021
Tianjin, China
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