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

机译:集成到红外光源的纹理分析,可识别数字光弹性中的高条纹浓度

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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.
机译:在数字光弹性图像中,具有高条纹密度的区域代表了在应力图的特定区域展开相位的限制。在这项工作中,我们在基于圆偏振镜观察直径压缩下的双折射盘的模拟实验中,通过将光源波长从可见光更改为远红外线来识别这些区域。识别过程包括在可见电磁波谱和红外的不同子带中评估应用于从合成图像的感兴趣区域提取的数据集的纹理描述符的相关性。我们的结果表明,将光弹性组件扩展到远红外线,可以在高条纹浓度的区域中解决应力场。此外,我们表明,纹理描述符可以克服与条纹集中在可见光谱而不是红外集中的区域中的高应力值识别相关的限制。

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