Computational Detection of Salient Information to Identify High Stress and Ambiguity Regions in Digital Photoelasticity Images

Juan C. Briñez de León; Diego A. Patiño; Alejandro Restrepo M; John W. Branch

doi:10.1364/ISA.2017.IM4E.2

Imaging and Applied Optics 2017 (3D, AIO, COSI, IS, MATH, pcAOP)
OSA Technical Digest (online) (Optica Publishing Group, 2017),
paper IM4E.2
•https://doi.org/10.1364/ISA.2017.IM4E.2

Computational Detection of Salient Information to Identify High Stress and Ambiguity Regions in Digital Photoelasticity Images

Juan C. Briñez de León, Diego A. Patiño, Alejandro Restrepo M, and John W. Branch

Imaging Systems and Applications 2017

San Francisco, California United States
26–29 June 2017
ISBN: 978-1-943580-29-3

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Image Processing and Applications (IM4E)

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J. C. Briñez de León, D. A. Patiño, A. R. M, and J. W. Branch, "Computational Detection of Salient Information to Identify High Stress and Ambiguity Regions in Digital Photoelasticity Images," in Imaging and Applied Optics 2017 (3D, AIO, COSI, IS, MATH, pcAOP), OSA Technical Digest (online) (Optica Publishing Group, 2017), paper IM4E.2.

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Abstract

Identifying ambiguities and high stress regions in digital photoelasticity is a complex process. We consider such zones as salient information, and process them through saliency algorithms. Hence, highlighted information coincided with ambiguities and stress concentrations.

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