Texture analysis integrated to infrared light sources for identifying high fringe concentrations in digital photoelasticity

Hermes Fandiño Toro; Juan Carlos Briñez de León; Alejandro Restrepo Martínez; John W. Branch Bedoya

doi:10.1117/12.2273258

19 September 2017 Texture analysis integrated to infrared light sources for identifying high fringe concentrations in digital photoelasticity

Hermes Fandiño Toro, Juan Carlos Briñez de León, Alejandro Restrepo Martínez, John W. Branch Bedoya

Author Affiliations +

Proceedings Volume 10396, Applications of Digital Image Processing XL; 103962D (2017) https://doi.org/10.1117/12.2273258
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

In digital photoelasticity images, regions with high fringe densities represent a limitation for unwrapping the phase in specific zones of the stress map. In this work, we recognize such regions by varying the light source wavelength from visible to far infrared, in a simulated experiment based on a circular polariscope observing a birefringent disk under diametral compression. The recognition process involves evaluating the relevance of texture descriptors applied to data sets extracted from regions of interest of the synthetic images, in the visible electromagnetic spectrum and different sub-bands of the infrared. Our results show that extending photoelasticity assemblies to the far infrared, the stress fields could be resolved in regions with high fringe concentrations. Moreover, we show that texture descriptors could overcome limitations associated to the identification of high-stress values in regions in which the fringes are concentrated in the visible spectrum, but not in the infrared.

Citation Download Citation

Hermes Fandiño Toro, Juan Carlos Briñez de León, Alejandro Restrepo Martínez, and John W. Branch Bedoya "Texture analysis integrated to infrared light sources for identifying high fringe concentrations in digital photoelasticity", Proc. SPIE 10396, Applications of Digital Image Processing XL, 103962D (19 September 2017); https://doi.org/10.1117/12.2273258

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available