Acquiring and processing light deflection maps for transparent object inspection

2016 ◽  
Author(s):  
Johannes Meyer ◽  
Thomas Langle ◽  
Jurgen Beyerer
Keyword(s):  
Light Deflection ◽  
Transparent Object ◽  
Object Inspection

SNR-optimized image fusion for transparent object inspection

2018 ◽  
Author(s):  
Johannes Meyer ◽  
Wolfgang Melchert ◽  
Matthias Hartrumpf ◽  
Thomas Längle ◽  
Jürgen Beyerer
Keyword(s):  
Image Fusion ◽  
Transparent Object ◽  
Object Inspection

About acquiring and processing light transport matrices for transparent object inspection

2016 ◽  
Vol 83 (12) ◽  
Author(s):  
Johannes Meyer ◽  
Thomas Längle ◽  
Jürgen Beyerer
Keyword(s):  
Test Object ◽  
Visual Inspection ◽  
Dark Field ◽  
Light Transport ◽  
Air Bubbles ◽  
Physically Based ◽  
Inspection Systems ◽  
Transparent Object ◽  
Transparent Materials ◽  
Object Inspection

AbstractTransparent materials are employed for creating different kinds of products and have to meet high quality requirements. First of all, transparent materials have to be free from scattering defects, e.g., enclosed air bubbles. Visual inspection systems based on dark field setups are principally capable of imaging these kinds of defects, however, it usually requires much effort to adapt them to the test object on hand. This article shows how light transport matrices can be calculated for an optical system consisting of a programmable area light source and a telecentric camera. Two features are proposed that can be extracted out of these matrices and that allow to image scattering defects present in a transparent object without the need of adapting the system to the actual test object. The results of synthetic experiments obtained using a physically based and adequately extended rendering framework approved the proposed approach and showed that it even outperforms classical inspection systems in some situations.

scholarly journals Specular Reflection Detection and Inpainting in Transparent Object through MSPLFI

2021 ◽  
Vol 13 (3) ◽  
pp. 455
Author(s):  
Md Nazrul Islam ◽  
Murat Tahtali ◽  
Mark Pickering
Keyword(s):  
Light Field ◽  
Mean Squared Error ◽  
Specular Reflection ◽  
Similarity Index ◽  
Detection Algorithm ◽  
Color Channel ◽  
Absolute Deviation ◽  
Significant Information ◽  
Transparent Objects ◽  
Transparent Object

Multispectral polarimetric light field imagery (MSPLFI) contains significant information about a transparent object’s distribution over spectra, the inherent properties of its surface and its directional movement, as well as intensity, which all together can distinguish its specular reflection. Due to multispectral polarimetric signatures being limited to an object’s properties, specular pixel detection of a transparent object is a difficult task because the object lacks its own texture. In this work, we propose a two-fold approach for determining the specular reflection detection (SRD) and the specular reflection inpainting (SRI) in a transparent object. Firstly, we capture and decode 18 different transparent objects with specularity signatures obtained using a light field (LF) camera. In addition to our image acquisition system, we place different multispectral filters from visible bands and polarimetric filters at different orientations to capture images from multisensory cues containing MSPLFI features. Then, we propose a change detection algorithm for detecting specular reflected pixels from different spectra. A Mahalanobis distance is calculated based on the mean and the covariance of both polarized and unpolarized images of an object in this connection. Secondly, an inpainting algorithm that captures pixel movements among sub-aperture images of the LF is proposed. In this regard, a distance matrix for all the four connected neighboring pixels is computed from the common pixel intensities of each color channel of both the polarized and the unpolarized images. The most correlated pixel pattern is selected for the task of inpainting for each sub-aperture image. This process is repeated for all the sub-aperture images to calculate the final SRI task. The experimental results demonstrate that the proposed two-fold approach significantly improves the accuracy of detection and the quality of inpainting. Furthermore, the proposed approach also improves the SRD metrics (with mean F1-score, G-mean, and accuracy as 0.643, 0.656, and 0.981, respectively) and SRI metrics (with mean structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), mean squared error (IMMSE), and mean absolute deviation (MAD) as 0.966, 0.735, 0.073, and 0.226, respectively) for all the sub-apertures of the 18 transparent objects in MSPLFI dataset as compared with those obtained from the methods in the literature considered in this paper. Future work will exploit the integration of machine learning for better SRD accuracy and SRI quality.

scholarly journals The Celestial Reference System in Relativistic Framework

1990 ◽  
Vol 141 ◽  
pp. 99-110
Author(s):  
Han Chun-Hao ◽  
Huang Tian-Yi ◽  
Xu Bang-Xin
Keyword(s):  
Coordinate System ◽  
Reference Frame ◽  
Reference System ◽  
Light Deflection ◽  
Coordinate Systems ◽  
Definition Of ◽  
Celestial Sphere ◽  
Celestial Reference System ◽  
Relativistic Framework

The concept of reference system, reference frame, coordinate system and celestial sphere in a relativistic framework are given. The problems on the choice of celestial coordinate systems and the definition of the light deflection are discussed. Our suggestions are listed in Sec. 5.

scholarly journals Reactive underwater object inspection based on artificial electric sense

2016 ◽  
Vol 11 (4) ◽  
pp. 045003 ◽  
Author(s):  
Vincent Lebastard ◽  
Frédéric Boyer ◽  
Sylvain Lanneau
Keyword(s):  
Underwater Object ◽  
Object Inspection

scholarly journals On the efficient computation of the quadrupole light deflection

2010 ◽  
Vol 28 (1) ◽  
pp. 015009 ◽  
Author(s):  
Sven Zschocke ◽  
Sergei A Klioner
Keyword(s):  
Light Deflection ◽  
Efficient Computation
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