Fringe pattern analysis using deep learning

Photoelastic Fringe Pattern Analysis by Image Processing

This work presents a strategy for automatic analysis of photoelastic fringe patterns. The study is focused on the analysis of color type photoelastic fringes. By capturing and analyzing color fringes automatically, the difference between principal stresses of a sample are quantitatively determined. Among many techniques available in literature, the color photoelasticity is chosen as the basis f...

Fringe Pattern Demodulation Using Evolutionary Algorithms

Topic Based Sentiment Analysis Using Deep Learning

In this paper , we tackle Sentiment Analysis conditioned on a Topic in Twitter data using Deep Learning . We propose a 2-tier approach : In the first phase we create our own Word Embeddings and see that they do perform better than state-of-the-art embeddings when used with standard classifiers. We then perform inference on these embeddings to learn more about a word with respect to all the topi...

Windowed Fourier transform for fringe pattern analysis: addendum.

Novel approaches based on windowed Fourier transform for demodulation of fringe patterns were previously presented [Appl. Opt. 43, 2695-2702 (2004)], where extraction of phase and phase derivatives from either phase-shifted fringe patterns or a single-carrier fringe pattern was the main focus. I show that the same methods can be applied to process a single closed-fringe pattern in either noise ...

Atmospheric tomography using a fringe pattern in the sodium layer.

We wish to measure and separate the contribution of atmospheric turbulent layers for multiconjugate adaptive optics. To this end, we propose to create a periodic fringe pattern in the sodium layer and image it with a modified Hartmann sensor. Overlapping sections of the fringes are imaged by a lenslet array onto contiguous areas in a large-format camera. Low-layer turbulence causes an overall s...