Fringe pattern analysis to evaluate light sources and sensors in digital photoelasticity

When experimental photoelasticity images are acquired, the spectral interaction between the light source and the sensor used affect the visual information of the fringe patterns in the produced images. Such interaction can lead to fringe patterns with an overall high quality, but also can lead to images with indistinguishable fringes, and bad stress field reconstruction. We introduce a strategy to evaluate such interaction that relies on measuring the value of four handcrafted descriptors: contrast, an image descriptor that accounts simultaneously for blur and noise, a Fourier-based descriptor to measure image quality, and image entropy. The utility of the proposed strategy was validated by measuring the selected descriptors on computational photoelasticity images, and the fringe orders achieved when evaluating the stress field, from 240 spectral configurations: 24 light sources and 10 sensors. We found that high values of the selected descriptors can be related to spectral configurations that lead to better stress field reconstruction. Overall, the results show that the selected descriptors can be useful to identify bad and good spectral interactions, which could help to design better protocols for acquiring photoelasticity images.