Instantaneous Spatial Phase-Stepping Methods for Phase-Measuring Interferometry and Photoelasticity

This paper demonstrates instantaneous phase-stepping and subsequent phase analysis methods for interferometry and two-dimensional photoelasticity. The camera that has a pixelated form-birefringent micro-retarder array acquires phase-stepped fringes in a single camera frame. Then, the distributions of Stokes parameters that represent the state of polarization are calculated from a single image. In the case of the polarization interferometer, the phase difference of the two orthogonally polarized light beam can be easily determined from the Stokes parameters. On the other hand, the phase distributions of the isochromatics and the isoclinics are obtained in the case of the photoelasticity. It is emphasized that this method is applicable to real-time inspection of optical elements as well as the study of the mechanics of time-dependent materials because multiple exposures are unnecessary for sufficient data acquisition in the completion of data analysis.

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Full Measurement of the Stokes Parameters Using a Subwavelength Silicon On-Chip Polarimeter

Advances in Science and Technology ◽

10.4028/www.scientific.net/ast.98.103 ◽

2016 ◽

Vol 98 ◽

pp. 103-108

Author(s):

Alba Espinosa-Soria ◽

Francisco J. Rodríguez-Fortuño ◽

Amadeu Griol ◽

Alejandro Martínez

Keyword(s):

Light Beam ◽

Stokes Parameters ◽

Plasmonic Nanostructures ◽

Spin Orbit Coupling ◽

Metallic Elements ◽

Optical Elements ◽

Half Wave ◽

State Of Polarization ◽

Technological Platform ◽

On Chip

Polarimetry enables to measure the state of polarization (SoP) of a light beam, which is essential in many disciplines. Typical polarimeters use bulky and expensive optical elements such as half-wave plates and grid polarizers. Plasmonic nanostructures may help to transform such bulky components into subwavelength metallic elements showing similar performance. Based on the concept of spin-orbit coupling, here we demonstrate a nanophotonic polarimeter that measures the Stokes parameters of a light beam over an ultrabroad bandwidth in a less than a square wavelength active region. Furthermore, the presented approach is applicable to any wavelength regime and technological platform, paving the way for the miniaturization of polarimeters.

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Fast 3D Rotation Estimation of Fruits Using Spheroid Models

Sensors ◽

10.3390/s21062232 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2232

Author(s):

Antonio Albiol ◽

Alberto Albiol ◽

Carlos Sánchez de Merás

Keyword(s):

Fruit Quality ◽

3D Model ◽

Geometric Model ◽

Fruit Shape ◽

Single Camera ◽

Global Score ◽

Topographic Map ◽

Single Image ◽

Large Effort ◽

Fruit Surface

Automated fruit inspection using cameras involves the analysis of a collection of views of the same fruit obtained by rotating a fruit while it is transported. Conventionally, each view is analyzed independently. However, in order to get a global score of the fruit quality, it is necessary to match the defects between adjacent views to prevent counting them more than once and assert that the whole surface has been examined. To accomplish this goal, this paper estimates the 3D rotation undergone by the fruit using a single camera. A 3D model of the fruit geometry is needed to estimate the rotation. This paper proposes to model the fruit shape as a 3D spheroid. The spheroid size and pose in each view is estimated from the silhouettes of all views. Once the geometric model has been fitted, a single 3D rotation for each view transition is estimated. Once all rotations have been estimated, it is possible to use them to propagate defects to neighbor views or to even build a topographic map of the whole fruit surface, thus opening the possibility to analyze a single image (the map) instead of a collection of individual views. A large effort was made to make this method as fast as possible. Execution times are under 0.5 ms to estimate each 3D rotation on a standard I7 CPU using a single core.

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Modification of diffraction pattern of a slit using polarized light having variable state of polarization

Journal of Optics ◽

10.1007/s12596-011-0042-0 ◽

2011 ◽

Vol 40 (3) ◽

pp. 101-106

Author(s):

Mohammad Tahir ◽

K. Bhattacharya ◽

A. K. Chakraborty

Keyword(s):

Diffraction Pattern ◽

Polarized Light ◽

State Of Polarization

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Reconstruction of the probability density function by means of the degree of polarization for one-photon mixed states

Open Physics ◽

10.2478/s11534-013-0185-5 ◽

2013 ◽

Vol 11 (4) ◽

Author(s):

Lukasz Michalik ◽

Andrzej Domanski

Keyword(s):

Probability Density ◽

Thought Experiment ◽

Reference Beam ◽

Quantum Tomography ◽

Stokes Parameters ◽

Degree Of Polarization ◽

Probability Density Distribution ◽

Mixed States ◽

State Of Polarization ◽

Linear Polarizer

AbstractIn this paper the authors discuss an alternative way for reconstructing one-photon mixed states of a partially polarized optical field. The task is to represent the probability density distribution describing these kind of states with the Stokes parameters which also characterize the effective state of polarization. These parameters can be measured by means of the degree of polarization with an experimental setup containing a rotating linear polarizer and a circular polarizer. A thought experiment is presented which assumes that the measurement is undertaken on an analyzed beam coupled with a reference beam containing photons polarized in a well-known way. The method discussed in the paper is an alternative for the most commonly used quantum tomography approach.

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Diffraction of polarized light by the real diffractive optical elements

10.1117/12.192042 ◽

1994 ◽

Author(s):

Jan Popelek ◽

Frantisek Urban ◽

Ludmila Vrestalova

Keyword(s):

Polarized Light ◽

Diffractive Optical Elements ◽

Optical Elements ◽

The Real

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A Vision-based navigation system for landing procedure

ACTA IMEKO ◽

10.21014/acta_imeko.v7i2.533 ◽

2018 ◽

Vol 7 (2) ◽

pp. 102 ◽

Cited By ~ 3

Author(s):

Silvio Del Pizzo ◽

Umberto Papa ◽

Salvatore Gaglione ◽

Salvatore Troisi ◽

Giuseppe Del Core

Keyword(s):

Navigation System ◽

Gps Tracking ◽

Single Camera ◽

Control Points ◽

Single Image ◽

Precise Position ◽

Image Frame ◽

Vision Based Navigation ◽

Moving Platform ◽

Image Camera

An autonomous vision-based landing system was designed and its performance is analysed and measured by an UAS. The system equipment is based on a single camera to determine its position and attitude with respect to a well-defined landing pattern. The developed procedure is based on photogrammetric Space Resection Solution, which provides the position and camera attitude reckoning starting from at least three, not aligned, reference control points whose image coordinates may be measured in the image camera frame. Five circular coloured targets were placed on a specific landing pattern, their 2D image frame coordinates was extracted through a particular algorithm. The aim of this work is to compute UAS precise position and attitude from single image, in order to have a good approach to landing field. This procedure can be used in addition or for replacement of GPS tracking and can be applied when the landing field is movable or located on a moving platform, the UAS will follow the landing pattern until the landing phase will be closed.

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Can we Localize an AV from a Single Image? Deep-Geometric 6 DoF Localization in Topo-metric Maps

Journal of Autonomous Vehicles and Systems ◽

10.1115/1.4052604 ◽

2021 ◽

pp. 1-13

Author(s):

Punarjay Chakravarty ◽

Tom Roussel ◽

Gaurav Pandey ◽

Tinne Tuytelaars

Keyword(s):

Pose Estimation ◽

Autonomous Vehicles ◽

Hybrid Algorithm ◽

Degrees Of Freedom ◽

Single Camera ◽

Single Image ◽

Six Degrees Of Freedom ◽

Localization Algorithms ◽

Mapping Process ◽

Set Of Points

Abstract We describe a Deep-Geometric Localizer that is able to estimate the full six degrees-of-freedom (DoF) global pose of the camera from a single image in a previously mapped environment. Our map is a topo-metric one, with discrete topological nodes whose 6DOF poses are known. Each topo-node in our map also comprises of a set of points, whose 2D features and 3D locations are stored as part of the mapping process. For the mapping phase, we utilise a stereo camera and a regular stereo visual SLAM pipeline. During the localization phase, we take a single camera image, localize it to a topological node using Deep Learning, and use a geometric algorithm (PnP) on the matched 2D features (and their 3D positions in the topo map) to determine the full 6DOF globally consistent pose of the camera. Our method divorces the mapping and the localization algorithms and sensors (stereo and mono), and allows accurate 6DOF pose estimation in a previously mapped environment using a single camera. With results in simulated and real environments, our hybrid algorithm is particularly useful for autonomous vehicles (AVs) and shuttles that might repeatedly traverse the same route.

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