Advanced PIV algorithms Why and when advanced PIV algorithms?
|
|
- Martin Bryant
- 5 years ago
- Views:
Transcription
1 Advanced PIV algorithms Why and when advanced PIV algorithms? Speaker: Antonio Lecuona, Prof. Contributors: Dr. José I. Nogueira, Dr. Ángel Velázquez, A. Acosta, D. Santana, Prof. P. A. Rodríguez, Dr. U. Ruiz-Rivas, B. Méndez. Universidad Carlos III de Madrid, PIVNET 2/Ercoftac SIG 32 workshop Lisbon, 5 th and 6 th July
2 Contents I. Standard PIV algorithms II. III. Image distortion algorithms Advanced post-processing of PIV data based on the Navier-Stokes equations 2
3 I. Standard (correlation) PIV 1. Interrogation window 2. Cross-correlation using FFT or DC 3. Peak detection 4. Subpixel peak fitting s 3
4 I. Standard PIV (cont.) Basic parameters: ( for physical variables) Image sampling: pixel size p Group sampling: Window size F Grid distance, overlapping o = /F ) Flow sampling: particle diameter d and average distance δ Time sampling: inter-image time delay t = 1 Flowfield spatial frequency: λ gradients Usually p is the measuring unit s = f (F,, d, δ, λ,addit. parameters) Additional parameters: Imaging noise (interlacing, pattern, pixel blinds, blooming, ), Optical noise (laser interferences, stray light, reflections and shades), Optical deformations and aberrations, Laser plane non coincidence, Out of plane pair losses, Particle seeding inhomogeneities, Numerical noise. 4
5 I. Standard PIV (cont.) Peak locking: Sources d < 2, particle image undersampling interchangeable with random error (unavoidable). F 1 Particle truncation at window borders, relevant for extreme multigrid (avoidable ). Effects Particularly relevant for small s. Creates non rotating star-like structures with 4, 8.. arms in vortices. Peak fitting accuracy and high flow field sampling (small δ) call for small d near peak locking operation. 5
6 I. Standard PIV (cont.) First advancement: Window shift: compensation of the average s s < 0,5 increase in s/n and accuracy, if in the correct direction). First need of iteration! 6
7 I. Standard PIV (cont.) Standard PIV limits: Physical: δ > d; Nyquist λ > 2δ Amplitude response: δ F λ 1,7 F (in figure 3) Detectability: δ (π N min /4) -1/2 F N min = minimum # particles for peak detection N min Multigrid Aplicable λ Multigrid methods progressively reduce w to increase spatial frequency resolution overcoming amplitude response criterion. N min (F/λ) n detectability limits could arrive first when resolving λ. Line: F λ 7
8 I. Standard PIV (cont.) Aggregation of particle pair peaks: I. A pair peak contributes to the main peak if s m = main peak displacement. s p = pair peak displacement. sm -s p < R + wp min = 3 w p R = radius considered in the peak fitting algorithm. R w p = pair peak waist d/ 2 Consequences: s m -s p I. Large particles and low disp. differences window moving averaging II. III. Small particles and high disp. differences no averaging Intermediate case non linear amplitude response and group locking IV. The most distant peaks are dropped non linear response 8
9 I. Standard PIV (cont.) Examples of group locking I. 1D Linear gradient (spurious peaks eliminated) Grad F/2 Displacement 4 particle peaks Many particles peaks Actually, there is no group locking in this example but uncertainty, unless there is particle a region with the same displacement. 1D Sinusoidal displacement Grad F Group locking Displacement 4 particle peaks Many particles peaks 9
10 I. Standard PIV (cont.) Examples of group locking Correlation plane of 1D sinusoidal displacement, d = 2,5; R = 1,5; F = s = 4 s = 4 s =16 Noiseless gaussian particles randomly located 10
11 I.Standard PIV (cont.) Group locking: a local detection algorithm 1 G = > s s x y s s x y + + x x y y When in a window G is large, it signals the displacement group locking. For 1D sinusoidal displacement Deep areas indicate group lockers Clear areas do not contribute to the peak unless s m -s p < R + w p This effect is negligible for F/λ << 1 because s m -s p vanishes (windows will have the same colour). A qualitative error measure in a window is σ G, but is not computable form PIV data. 11
12 I.Standard PIV (cont.) Examples of group locking (cont.) PIV obtained results 1D Sinusoidal displac. (cont. line input, red line model, points PIV output) Displacement (pixels) Displacement (pixels) Displacement (pixels) Location (pixels) Location (pixels) Location (pixels) λ/f = λ/f = 2 λ/f = 1 Synthetic vortex (G in yellow, int. win. in blue) = 4; d = 2,5; δ = 2; λ= 65,6; A = 4,5. s = Acos(2 πx/ λ)sin(2 π y/ λ) x s = Asin(2 πx/ λ)cos(2 π y/ λ) y F = 16 F = 32 12
13 I.Standard PIV (cont.) Amplitude response to 1D sinusoidal displacement field First armonic relative amplitude A C B Circles F = 64. Squares F =32. Empty symbols: Clean images. Filled symbols: Noisy images. Continuous line: moving average amplitude response. Discontinuous line squares indicate the displacement distribution within the interrogation window, not to scale. Normalised window size F /λ Figure 3.- The average 1D amplitude responses of single step PIV without window weighting function. The amplitude response is higher than moving average. This is explained by group locking. Regions of negative response Window shift in the opposite direction For F/λ I amplitude response is statistically 0, but could be ±1 owing to group locking high uncertainty. 13
14 I. Standard PIV (cont.) Conclusions: I. Correlation PIV with no image distortion is accurate only when peak overlapping is assured s m -s p < R + w p. It is not equivalent to the rule of thumb ( s max - s min )/F < 5% although it is generally fulfilled. II. Group locking appears in the first stages of multigrid and image distortion PIV. III. Group locking introduces non-linearities that increase SNR. Solutions: I. Multigrid PIV: iterative reduction of F incurring in loss of robustness. II. Image distortion: Iteratively reduces s m -s p so that peak aggregation increases SNR and non-linearities are reduced. Window distortion is a partial application of image distortion. δ Resulting in a wider N min area of application: Aplicable λ 14
15 II. Image distortion algorithms The main purpose is to reduce s m -s p thus increasing SNR and reducing group locking. At the end s 0 would result. Negative amplitude response could induce divergence instability. Solutions to instability: Window weighting (LFC-PIV) effective, but there is a small error. Alliasing reduction compromise between spatial resolution and robustness. Averaging reduces spatial resolution. Its amplitude response is negative for some λ. 15
16 II. Image distortion algorithms (cont.) + LFC-PIV Correlation Image a* + Correlation + Previous measurements Image a Compensation of the particle pattern deformaton Image b* Image a* Image b Compensation of the particle pattern deformaton after several iterations (15 in this case) Image b* Sketch of the LFCPIV iterative procedure. Black dots represent particle images in negative, grid-like distributed in order to show the particle pattern deformation. No error would yield a perfect cross ruled particle pattern after processing. Grey grid is for reference only, showing a rotation in the middle of the image and a shear at the borders after the compensation. Framed images represent actual measured displacement fields. Long horizontal arrows represent LFCPIV processing after 1, 2 and 15 iterations. Grid spacing is 16 pixels. 16
17 II. Image distortion algorithms (cont.) Example of results obtained with LFC-PIV Original image LFC, F = 64, λ = 65,6 17
18 II. Image distortion algorithms (cont.) Example of results obtained with LFC-PIV Vorticity map based on LFC PIV data with grid distance of 8 pixels. DLR provided image. F = 64 18
19 II. Image distortion algorithms (cont.) Conclusions: Image distortion widens the applicability of correlation PIV Reduces: Low pass window effects Group locking Increases: SNR Spatial resolution Computing time Still under development: Instabilities and error growth 19
20 III. Advanced post-processing of PIV data based on the Navier-Stokes equations Normally carried out using statistics based methodologies (filters, interpolators, etc.) An alternate approach is to devise a post-processing methodology that is based on the Physics of the problem (that is: on the Navier-Stokes equations) This alternate approach is very challenging from a technical standpoint but, if successful, the potential benefits for practical industrial applications could be significant. Accuracy of PIV predictions could increase by a sizable margin. 20
21 A 2D Navier-Stokes based PIV Post-processing methodology has to be dependent on a very robust and flexible computational algorithm. A good candidate that fulfils these requirements is a gridless (loose connectivity) formulation. Close up view of the mesh around a cylinder at Re = 500. Results: C d experimental =1.16, C d numerical = Different topologies can be used simultaneously (left) Random placement is feasible (right) 21
22 Reconstruction of the full Navier-Stokes flow field (Re = 100, M = 0) around a cylinder. 200 randomly scattered points outside the boundary layer were used to provide seed velocity information ( simulating tracking PIV) Reconstructed pressure profile θ Reconstructed shear stress C d experimental: 1.46, C d reconstructed: 1.44 Experimental separation point: 110 deg. Reconstructed separation point: 120 deg θ 22
23 To check the numerical robustness of the method, 5 % of the 200 seed points were perturbed ± 10 % in their velocity components. A slight deterioration of the reconstruction was observed. A finer resolution is needed for this case. C dexp = 1.46, C drecons = 1.44 Separation point: exper. = 110 deg, recons. = 120 deg C dexp = 1.46, C drecons = 1.47 Separation point: exper. = 110 deg, recons. = 127 deg 23
Assessment of Vorticity with Advanced PIV Techniques
Assessment of Vorticity with Advanced PIV Techniques A. Lecuona, J. Nogueira, A. Acosta and P. A. Rodríguez. Dep. of Thermal and Fluids Engineering, Univ. Carlos III de Madrid. c/ Butarque 15, 28911-Leganés,
More informationParticle Image Velocimetry for Fluid Dynamics Measurements
Particle Image Velocimetry for Fluid Dynamics Measurements Lyes KADEM, Ph.D; Eng kadem@encs.concordia.ca Laboratory for Cardiovascular Fluid Dynamics MIE Concordia University Presentation - A bit of history
More information9.9 Coherent Structure Detection in a Backward-Facing Step Flow
9.9 Coherent Structure Detection in a Backward-Facing Step Flow Contributed by: C. Schram, P. Rambaud, M. L. Riethmuller 9.9.1 Introduction An algorithm has been developed to automatically detect and characterize
More informationThe Elimination of Correlation Errors in PIV Processing
9 th International Symposium on Applications of Laser Techniques to Fluid Mechanics, Lisbon, Portugal, July, 1998 The Elimination of Correlation Errors in PIV Processing Douglas P. Hart Massachusetts Institute
More informationOn the stabilization and spatial resolution of iterative PIV interrogation. Ferry F.J. Schrijer and Fulvio Scarano
On the stabilization and spatial resolution of iterative PIV interrogation Ferry F.J. Schrijer and Fulvio Scarano Department of Aerospace Engineering, Delft University of Technology, Delft, The Netherlands,
More informationTime-resolved PIV measurements with CAVILUX HF diode laser
Time-resolved PIV measurements with CAVILUX HF diode laser Author: Hannu Eloranta, Pixact Ltd 1 Introduction Particle Image Velocimetry (PIV) is a non-intrusive optical technique to measure instantaneous
More informationParticle Velocimetry Data from COMSOL Model of Micro-channels
Particle Velocimetry Data from COMSOL Model of Micro-channels P.Mahanti *,1, M.Keebaugh 1, N.Weiss 1, P.Jones 1, M.Hayes 1, T.Taylor 1 Arizona State University, Tempe, Arizona *Corresponding author: GWC
More informationParticle Image Velocimetry Part - 3
AerE 545X class notes #5 Particle Image Velocimetry Part - 3 Hui Hu Department of Aerospace Engineering, Iowa State University Ames, Iowa 50011, U.S.A PIV System Setup Particle tracers: Illumination system:
More informationA method to analyze molecular tagging velocimetry data using the Hough transform
REVIEW OF SCIENTIFIC INSTRUMENTS 86, 105106 (2015) A method to analyze molecular tagging velocimetry data using the Hough transform R. Sanchez-Gonzalez, 1,a) B. McManamen, 2 R. D. W. Bowersox, 2 and S.
More informationModule 3: Velocity Measurement Lecture 14: Analysis of PIV data. The Lecture Contains: Flow Visualization. Test Cell Flow Quality
The Lecture Contains: Flow Visualization Test Cell Flow Quality Influence of End-Plates Introduction To Data Analysis Principle of Operation of PIV Various Aspects of PIV Measurements Recording of the
More informationMeasurement Techniques. Digital Particle Image Velocimetry
Measurement Techniques Digital Particle Image Velocimetry Heat and Mass Transfer Laboratory (LTCM) Sepideh Khodaparast Marco Milan Navid Borhani 1 Content m Introduction m Particle Image Velocimetry features
More informationScanner Parameter Estimation Using Bilevel Scans of Star Charts
ICDAR, Seattle WA September Scanner Parameter Estimation Using Bilevel Scans of Star Charts Elisa H. Barney Smith Electrical and Computer Engineering Department Boise State University, Boise, Idaho 8375
More informationHydrodynamic Instability and Particle Image Velocimetry
Hydrodynamic Instability and Particle Image Velocimetry Instabilities in lid-driven cavities First important investigations of hydrodynamic instabilities were published by v. Helmholtz (1868), Lord Rayleigh
More informationFlow Structures Extracted from Visualization Images: Vector Fields and Topology
Flow Structures Extracted from Visualization Images: Vector Fields and Topology Tianshu Liu Department of Mechanical & Aerospace Engineering Western Michigan University, Kalamazoo, MI 49008, USA We live
More informationWe N Converted-phase Seismic Imaging - Amplitudebalancing Source-independent Imaging Conditions
We N106 02 Converted-phase Seismic Imaging - Amplitudebalancing -independent Imaging Conditions A.H. Shabelansky* (Massachusetts Institute of Technology), A.E. Malcolm (Memorial University of Newfoundland)
More informationInfluence of number of cameras and preprocessing for thick volume Tomographic PIV. Yuichi Fukuchi
Influence of number of cameras and preprocessing for thick volume Tomographic PIV Yuichi Fukuchi Fundamental technology research center division 3, Honda R&D, Saitama, Japan Yuuichi_fukuchi@n.f.rd.honda.co.jp
More informationNeurophysical Model by Barten and Its Development
Chapter 14 Neurophysical Model by Barten and Its Development According to the Barten model, the perceived foveal image is corrupted by internal noise caused by statistical fluctuations, both in the number
More informationVolumetric Velocimetry via Scanning Back-Projection and Least-Squares-Matching Algorithms of a Vortex Ring
Volumetric Velocimetry via Scanning Back-Projection and Least-Squares-Matching Algorithms of a Vortex Ring Benjamin Ponitz 1,*, Mark Sastuba 1, Christoph Brücker 1 and Jens Kitzhofer 2 1: Institute of
More informationFlow structure and air entrainment mechanism in a turbulent stationary bore
Flow structure and air entrainment mechanism in a turbulent stationary bore Javier Rodríguez-Rodríguez, Alberto Aliseda and Juan C. Lasheras Department of Mechanical and Aerospace Engineering University
More informationSUPPLEMENTARY INFORMATION
SUPPLEMENTARY INFORMATION doi:10.1038/nature10934 Supplementary Methods Mathematical implementation of the EST method. The EST method begins with padding each projection with zeros (that is, embedding
More information4th International PIV Challenge cases C and D Contents
4th International PIV Challenge cases C and D Contents 4th International PIV Challenge cases C and D... 2 1 General recommendation... 2 1.1 Calibration... 2 1.2 Self calibration... 3 1.3 Tomographic reconstruction...
More informationFlow Field of Truncated Spherical Turrets
Flow Field of Truncated Spherical Turrets Kevin M. Albarado 1 and Amelia Williams 2 Aerospace Engineering, Auburn University, Auburn, AL, 36849 Truncated spherical turrets are used to house cameras and
More informationContrast Optimization A new way to optimize performance Kenneth Moore, Technical Fellow
Contrast Optimization A new way to optimize performance Kenneth Moore, Technical Fellow What is Contrast Optimization? Contrast Optimization (CO) is a new technique for improving performance of imaging
More informationPulsating flow around a stationary cylinder: An experimental study
Proceedings of the 3rd IASME/WSEAS Int. Conf. on FLUID DYNAMICS & AERODYNAMICS, Corfu, Greece, August 2-22, 2 (pp24-244) Pulsating flow around a stationary cylinder: An experimental study A. DOUNI & D.
More informationWind Tunnel Validation of Computational Fluid Dynamics-Based Aero-Optics Model
Wind Tunnel Validation of Computational Fluid Dynamics-Based Aero-Optics Model D. Nahrstedt & Y-C Hsia, Boeing Directed Energy Systems E. Jumper & S. Gordeyev, University of Notre Dame J. Ceniceros, Boeing
More informationUsing a multipoint interferometer to measure the orbital angular momentum of light
CHAPTER 3 Using a multipoint interferometer to measure the orbital angular momentum of light Recently it was shown that the orbital angular momentum of light can be measured using a multipoint interferometer,
More information3. Image formation, Fourier analysis and CTF theory. Paula da Fonseca
3. Image formation, Fourier analysis and CTF theory Paula da Fonseca EM course 2017 - Agenda - Overview of: Introduction to Fourier analysis o o o o Sine waves Fourier transform (simple examples of 1D
More informationEE795: Computer Vision and Intelligent Systems
EE795: Computer Vision and Intelligent Systems Spring 2012 TTh 17:30-18:45 FDH 204 Lecture 14 130307 http://www.ee.unlv.edu/~b1morris/ecg795/ 2 Outline Review Stereo Dense Motion Estimation Translational
More informationERROR RECOGNITION and IMAGE ANALYSIS
PREAMBLE TO ERROR RECOGNITION and IMAGE ANALYSIS 2 Why are these two topics in the same lecture? ERROR RECOGNITION and IMAGE ANALYSIS Ed Fomalont Error recognition is used to determine defects in the data
More informationElimination of peak-locking error in PIV analysis using the correlation mapping method
INSTITUTE OFPHYSICS PUBLISHING Meas. Sci. Technol. 1 (5) 15 118 MEASUREMENTSCIENCE AND TECHNOLOGY doi:1.188/957-/1/8/1 Elimination of peak-locking error in PIV analysis using the correlation mapping method
More informationDisplacement estimation
Displacement estimation Displacement estimation by block matching" l Search strategies" l Subpixel estimation" Gradient-based displacement estimation ( optical flow )" l Lukas-Kanade" l Multi-scale coarse-to-fine"
More informationThe Spalart Allmaras turbulence model
The Spalart Allmaras turbulence model The main equation The Spallart Allmaras turbulence model is a one equation model designed especially for aerospace applications; it solves a modelled transport equation
More information3D vector fields. Contents. Introduction 3D vector field topology Representation of particle lines. 3D LIC Combining different techniques
3D vector fields Scientific Visualization (Part 9) PD Dr.-Ing. Peter Hastreiter Contents Introduction 3D vector field topology Representation of particle lines Path lines Ribbons Balls Tubes Stream tetrahedra
More informationIMAGE PROCESSING IN PIV
ISTP-,, PRAGUE TH INTERNATIONAL SYMPOSIUM ON TRANSPORT PHENOMENA IMAGE PROCESSING IN PIV Milan Pěta, Jan Novotný Czech Technical University in Prague, Fakulty of Mechanical Engineering, Division of Fluid
More informationDevelopment of an Integrated Computational Simulation Method for Fluid Driven Structure Movement and Acoustics
Development of an Integrated Computational Simulation Method for Fluid Driven Structure Movement and Acoustics I. Pantle Fachgebiet Strömungsmaschinen Karlsruher Institut für Technologie KIT Motivation
More informationParticle Velocimetry Data from COMSOL Model of Micro-channels
Presented at the 2010 Boston Particle Velocimetry Data from COMSOL Model of Micro-channels P.Mahanti *,1, M.Keebaugh 1, N.Weiss 1, P.Jones 1, M.Hayes 1, T.Taylor 1 Arizona State University, Tempe, Arizona
More informationLagrangian 3D particle tracking for multi-pulse systems: performance assessment and application of Shake-The-Box
Lagrangian 3D particle tracking for multi-pulse systems: performance assessment and application of Shake-The-Box M. Novara 1,*, D. Schanz 1, S.Gesemann 1, K. Lynch 2, A. Schröder 1 1: Institute of Aerodynamics
More informationMotion Estimation for Video Coding Standards
Motion Estimation for Video Coding Standards Prof. Ja-Ling Wu Department of Computer Science and Information Engineering National Taiwan University Introduction of Motion Estimation The goal of video compression
More informationSUPPLEMENTARY FILE S1: 3D AIRWAY TUBE RECONSTRUCTION AND CELL-BASED MECHANICAL MODEL. RELATED TO FIGURE 1, FIGURE 7, AND STAR METHODS.
SUPPLEMENTARY FILE S1: 3D AIRWAY TUBE RECONSTRUCTION AND CELL-BASED MECHANICAL MODEL. RELATED TO FIGURE 1, FIGURE 7, AND STAR METHODS. 1. 3D AIRWAY TUBE RECONSTRUCTION. RELATED TO FIGURE 1 AND STAR METHODS
More informationMoving Interface Problems: Methods & Applications Tutorial Lecture II
Moving Interface Problems: Methods & Applications Tutorial Lecture II Grétar Tryggvason Worcester Polytechnic Institute Moving Interface Problems and Applications in Fluid Dynamics Singapore National University,
More informationImage Sampling and Quantisation
Image Sampling and Quantisation Introduction to Signal and Image Processing Prof. Dr. Philippe Cattin MIAC, University of Basel 1 of 46 22.02.2016 09:17 Contents Contents 1 Motivation 2 Sampling Introduction
More informationKeywords: flows past a cylinder; detached-eddy-simulations; Spalart-Allmaras model; flow visualizations
A TURBOLENT FLOW PAST A CYLINDER *Vít HONZEJK, **Karel FRAŇA *Technical University of Liberec Studentská 2, 461 17, Liberec, Czech Republic Phone:+ 420 485 353434 Email: vit.honzejk@seznam.cz **Technical
More informationImage Sampling & Quantisation
Image Sampling & Quantisation Biomedical Image Analysis Prof. Dr. Philippe Cattin MIAC, University of Basel Contents 1 Motivation 2 Sampling Introduction and Motivation Sampling Example Quantisation Example
More informationTHE SEVENTH ASIAN CONGRESS OF FLUID DYNAMICS DEC 8-12, 1997, MADRAS, INDIA VELOCITY FIELD MEASUREMENTS IN 3D ROTOR FLOWS
THE SEVENTH ASIAN CONGRESS OF FLUID DYNAMICS DEC 8-12, 1997, MADRAS, INDIA VELOCITY FIELD MEASUREMENTS IN 3D ROTOR FLOWS UC Reddy and NM Komerath School of Aerospace Engineering Georgia Institute of Technology
More informationLES Analysis on Shock-Vortex Ring Interaction
LES Analysis on Shock-Vortex Ring Interaction Yong Yang Jie Tang Chaoqun Liu Technical Report 2015-08 http://www.uta.edu/math/preprint/ LES Analysis on Shock-Vortex Ring Interaction Yong Yang 1, Jie Tang
More informationELEC Dr Reji Mathew Electrical Engineering UNSW
ELEC 4622 Dr Reji Mathew Electrical Engineering UNSW Review of Motion Modelling and Estimation Introduction to Motion Modelling & Estimation Forward Motion Backward Motion Block Motion Estimation Motion
More informationThe Role of 3D Measurements in the Understanding of Turbulent Boundary Layers
Coupled Atmosphere-Bushfire Modelling Workshop University of Melbourne, 16-18 May 2012 The Role of 3D Measurements in the Understanding of Turbulent Boundary Layers C. Atkinson, M. Kühn, N. Buchmann, D.
More informationVector Visualization. CSC 7443: Scientific Information Visualization
Vector Visualization Vector data A vector is an object with direction and length v = (v x,v y,v z ) A vector field is a field which associates a vector with each point in space The vector data is 3D representation
More informationFast Camera Image Analysis. B. A. Grierson
Fast Camera Image Analysis B. A. Grierson 9.28.2008 Introduction A high speed camera is used to image the visible light in. The camera is begins recording at the specified trigger time, and records until
More informationReduction of reconstructed particle elongation using iterative min-max filtering in holographic particle image velocimetry
Reduction of reconstructed particle elongation using iterative min-max filtering in holographic particle image velocimetry Yohsuke Tanaka 1, *, Shigeru Murata 1 1: Department of Mechanical System Engineering,
More informationSYNTHETIC SCHLIEREN. Stuart B Dalziel, Graham O Hughes & Bruce R Sutherland. Keywords: schlieren, internal waves, image processing
8TH INTERNATIONAL SYMPOSIUM ON FLOW VISUALIZATION (998) SYNTHETIC SCHLIEREN Keywords: schlieren, internal waves, image processing Abstract This paper outlines novel techniques for producing qualitative
More informationChange detection using joint intensity histogram
Change detection using joint intensity histogram Yasuyo Kita National Institute of Advanced Industrial Science and Technology (AIST) Information Technology Research Institute AIST Tsukuba Central 2, 1-1-1
More informationMichelson Interferometer
Michelson Interferometer The Michelson interferometer uses the interference of two reflected waves The third, beamsplitting, mirror is partially reflecting ( half silvered, except it s a thin Aluminum
More informationComputer Vision I. Announcements. Fourier Tansform. Efficient Implementation. Edge and Corner Detection. CSE252A Lecture 13.
Announcements Edge and Corner Detection HW3 assigned CSE252A Lecture 13 Efficient Implementation Both, the Box filter and the Gaussian filter are separable: First convolve each row of input image I with
More informationThree Dimensional Numerical Simulation of Turbulent Flow Over Spillways
Three Dimensional Numerical Simulation of Turbulent Flow Over Spillways Latif Bouhadji ASL-AQFlow Inc., Sidney, British Columbia, Canada Email: lbouhadji@aslenv.com ABSTRACT Turbulent flows over a spillway
More informationWhat makes Bolt Self-loosening Predictable?
What makes Bolt Self-loosening Predictable? Abstract Dr.-Ing. R. Helfrich, Dr.-Ing. M. Klein (INTES GmbH, Germany) In mechanical engineering, bolts are frequently used as standard fastening elements, which
More informationAn Embedded Boundary Method with Adaptive Mesh Refinements
An Embedded Boundary Method with Adaptive Mesh Refinements Marcos Vanella and Elias Balaras 8 th World Congress on Computational Mechanics, WCCM8 5 th European Congress on Computational Methods in Applied
More informationOverview: motion-compensated coding
Overview: motion-compensated coding Motion-compensated prediction Motion-compensated hybrid coding Motion estimation by block-matching Motion estimation with sub-pixel accuracy Power spectral density of
More informationGaussian Beam Calculator for Creating Coherent Sources
Gaussian Beam Calculator for Creating Coherent Sources INTRODUCTION Coherent sources are represented in FRED using a superposition of Gaussian beamlets. The ray grid spacing of the source is used to determine
More informationDEVELOPMENT OF ROBUST CORRELATION ALGORITHMS FOR IMAGE VELOCIMETRY USING ADVANCED FILTERING
DEVELOPMENT OF ROBUST CORRELATION ALGORITHMS FOR IMAGE VELOCIMETRY USING ADVANCED FILTERING by Adric Eckstein Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University
More informationSupplementary Materials for
advances.sciencemag.org/cgi/content/full/4/1/eaao7005/dc1 Supplementary Materials for Computational discovery of extremal microstructure families The PDF file includes: Desai Chen, Mélina Skouras, Bo Zhu,
More informationPerformance study on point target detection using super-resolution reconstruction
Performance study on point target detection using super-resolution reconstruction Judith Dijk a,adamw.m.vaneekeren ab, Klamer Schutte a Dirk-Jan J. de Lange a, Lucas J. van Vliet b a Electro Optics Group
More informationProf. Fanny Ficuciello Robotics for Bioengineering Visual Servoing
Visual servoing vision allows a robotic system to obtain geometrical and qualitative information on the surrounding environment high level control motion planning (look-and-move visual grasping) low level
More informationRealtime Water Simulation on GPU. Nuttapong Chentanez NVIDIA Research
1 Realtime Water Simulation on GPU Nuttapong Chentanez NVIDIA Research 2 3 Overview Approaches to realtime water simulation Hybrid shallow water solver + particles Hybrid 3D tall cell water solver + particles
More informationFLOW VISUALISATION OF POLYMER MELT CONTRACTION FLOWS FOR VALIDATION OF NUMERICAL SIMULATIONS
FLOW VISUALISATION OF POLYMER MELT CONTRACTION FLOWS FOR VALIDATION OF NUMERICAL SIMULATIONS R Spares, T Gough, M T Martyn, P Olley and P D Coates IRC in Polymer Science & Technology, Mechanical & Medical
More informationCreating an Automated Blood Vessel. Diameter Tracking Tool
Medical Biophysics 3970Z 6 Week Project: Creating an Automated Blood Vessel Diameter Tracking Tool Peter McLachlan - 250068036 April 2, 2013 Introduction In order to meet the demands of tissues the body
More informationMinimizing Noise and Bias in 3D DIC. Correlated Solutions, Inc.
Minimizing Noise and Bias in 3D DIC Correlated Solutions, Inc. Overview Overview of Noise and Bias Digital Image Correlation Background/Tracking Function Minimizing Noise Focus Contrast/Lighting Glare
More informationAlignment and Other Challenges in Reconstructing Cryotomograms with IMOD
Alignment and Other Challenges in Reconstructing Cryotomograms with IMOD Challenges in Cryotomography Alignment, alignment, alignment It can be hard to get fiducials onto/in the sample The low SNR makes
More informationCS 565 Computer Vision. Nazar Khan PUCIT Lectures 15 and 16: Optic Flow
CS 565 Computer Vision Nazar Khan PUCIT Lectures 15 and 16: Optic Flow Introduction Basic Problem given: image sequence f(x, y, z), where (x, y) specifies the location and z denotes time wanted: displacement
More informationSampling and Monte-Carlo Integration
Sampling and Monte-Carlo Integration Sampling and Monte-Carlo Integration Last Time Pixels are samples Sampling theorem Convolution & multiplication Aliasing: spectrum replication Ideal filter And its
More informationA Real-time Algorithm for Atmospheric Turbulence Correction
Logic Fruit Technologies White Paper 806, 8 th Floor, BPTP Park Centra, Sector 30, Gurgaon. Pin: 122001 T: +91-124-4117336 W: http://www.logic-fruit.com A Real-time Algorithm for Atmospheric Turbulence
More informationAccurately measuring 2D position using a composed moiré grid pattern and DTFT
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 Accurately measuring 2D position using a composed moiré grid pattern and DTFT S. Van
More informationComputer Graphics. Sampling Theory & Anti-Aliasing. Philipp Slusallek
Computer Graphics Sampling Theory & Anti-Aliasing Philipp Slusallek Dirac Comb (1) Constant & δ-function flash Comb/Shah function 2 Dirac Comb (2) Constant & δ-function Duality f(x) = K F(ω) = K (ω) And
More informationAn Experimental and Computational Investigation of a 3D, l/h=5 Transonic Cavity Flow. Prof Kevin Knowles Dr Simon Ritchie Dr Nick Lawson
An Experimental and Computational Investigation of a 3D, l/h=5 Transonic Cavity Flow Prof Kevin Knowles Dr Simon Ritchie Dr Nick Lawson Overview Background Experimental Studies Computational Studies Results
More informationCharacterisation of the interaction between a boundary layer and a cavity using Digital Particle Velocimetry with Optical Flow
Characterisation of the interaction between a boundary layer and a cavity using Digital Particle Velocimetry with Optical Flow G. Quénot*, A. Rambert**, P. Gougat**, T. Kowalevski*** *CLIPS-IMAG, Grenoble,
More informationMeasurement Principle What is VidPIV? An Overview of the VidPIV Interface Data Management
Measurement Principle What is VidPIV? An Overview of the Data Management Contents General Overview PIV Project 1 2 3 4 Measuring Principle 3 What is VidPIV? 4 An Overview of the 5 Data Management 6 4.1
More informationHPC Usage for Aerodynamic Flow Computation with Different Levels of Detail
DLR.de Folie 1 HPCN-Workshop 14./15. Mai 2018 HPC Usage for Aerodynamic Flow Computation with Different Levels of Detail Cornelia Grabe, Marco Burnazzi, Axel Probst, Silvia Probst DLR, Institute of Aerodynamics
More informationFormulas of possible interest
Name: PHYS 3410/6750: Modern Optics Final Exam Thursday 15 December 2011 Prof. Bolton No books, calculators, notes, etc. Formulas of possible interest I = ɛ 0 c E 2 T = 1 2 ɛ 0cE 2 0 E γ = hν γ n = c/v
More informationMichael Moody School of Pharmacy University of London 29/39 Brunswick Square London WC1N 1AX, U.K.
This material is provided for educational use only. The information in these slides including all data, images and related materials are the property of : Michael Moody School of Pharmacy University of
More informationINFLUENCE OF CURVATURE ILLUMINATION WAVEFRONT IN QUANTITATIVE SHEAROGRAPHY NDT MEASUREMENT
1 th A-PCNDT 6 Asia-Pacific Conference on NDT, 5 th 1 th Nov 6, Auckland, New Zealand INFLUENCE OF CURVATURE ILLUMINATION WAVEFRONT IN QUANTITATIVE SHEAROGRAPHY NDT MEASUREMENT Wan Saffiey Wan Abdullah
More informationPIV analysis around the Bilge Keel of a Ship Model in Free Roll Decay
PIV analysis around the Bilge Keel of a Ship Model in Free Roll Decay G.Aloisio *, F.Di Felice *. * INSEAN, Italian Ship Model Basin, Rome Abstract The results of an experimental analysis of the velocity
More informationUncertainty simulator to evaluate the electrical and mechanical deviations in cylindrical near field antenna measurement systems
Uncertainty simulator to evaluate the electrical and mechanical deviations in cylindrical near field antenna measurement systems S. Burgos*, F. Martín, M. Sierra-Castañer, J.L. Besada Grupo de Radiación,
More informationLAB 2: DATA FILTERING AND NOISE REDUCTION
NAME: LAB TIME: LAB 2: DATA FILTERING AND NOISE REDUCTION In this exercise, you will use Microsoft Excel to generate several synthetic data sets based on a simplified model of daily high temperatures in
More informationThe effect of a discrete window offset on the accuracy of cross-correlation analysis of digital PIV recordings
Experiments in Fluids 23 (1997) 20 28 Springer-Verlag 1997 The effect of a discrete window offset on the accuracy of cross-correlation analysis of digital PIV recordings J. Westerweel, D. Dabiri, M. Gharib
More informationPerformance evaluation of a Scheimpflug stereocamera for particle image velocimetry
Performance evaluation of a Scheimpflug stereocamera for particle image velocimetry Weijun Zang and Ajay K. Prasad We describe a novel stereocamera for particle image velocimetry PIV applications that
More informationDownloaded 09/01/14 to Redistribution subject to SEG license or copyright; see Terms of Use at
Random Noise Suppression Using Normalized Convolution Filter Fangyu Li*, Bo Zhang, Kurt J. Marfurt, The University of Oklahoma; Isaac Hall, Star Geophysics Inc.; Summary Random noise in seismic data hampers
More informationGCE AS and A Level. Physics A. AS exams 2009 onwards A2 exams 2010 onwards. Unit 3X: Approved specimen question paper. Version 1.0
GCE AS and A Level Physics A AS exams 2009 onwards A2 exams 2010 onwards Unit 3X: Approved specimen question paper Version 1.0 General Certificate of Education 2009 Advanced Subsidiary Examination abc
More information2 nd derivatives cross-correlation based PIV super-resolution
nd derivatives cross-correlation based PIV super-resolution by F. Scarano Delft University of Technology Department of Aerospace Engineering PO Box 558, 6 GB Delft; The Netherlands E-Mail: f.scarano@lr.tudelft.nl
More informationFast Multipole Method on the GPU
Fast Multipole Method on the GPU with application to the Adaptive Vortex Method University of Bristol, Bristol, United Kingdom. 1 Introduction Particle methods Highly parallel Computational intensive Numerical
More informationSubpixel Corner Detection Using Spatial Moment 1)
Vol.31, No.5 ACTA AUTOMATICA SINICA September, 25 Subpixel Corner Detection Using Spatial Moment 1) WANG She-Yang SONG Shen-Min QIANG Wen-Yi CHEN Xing-Lin (Department of Control Engineering, Harbin Institute
More informationHui Hu Department of Aerospace Engineering, Iowa State University Ames, Iowa 50011, U.S.A
AerE 311L & AerE343L Lecture Notes Lecture # 14: Advanced Particle Image Velocimetry Technique Hui Hu Department of Aerospace Engineering, Iowa State University Ames, Iowa 511, U.S.A Particle-based techniques:
More informationA three-dimensional velocimetry approach using a combination of tomographic reconstruction and triangulation for double-frame particle tracking
A three-dimensional velocimetry approach using a combination of tomographic reconstruction and triangulation for double-frame particle tracking Thomas Fuchs *, Rainer Hain, Christian J. Kähler Institute
More informationShock-Induced Instability Experiments on Gas Interfaces Featuring a Single Discrete Perturbation
Originally published in Proceedings of the Fifth International Workshop on Compressible Turbulent Mixing, ed. R. Young, J. Glimm & B. Boston. ISBN 9810229100, World Scientific (1996). Reproduced with the
More informationSimulation of In-Cylinder Flow Phenomena with ANSYS Piston Grid An Improved Meshing and Simulation Approach
Simulation of In-Cylinder Flow Phenomena with ANSYS Piston Grid An Improved Meshing and Simulation Approach Dipl.-Ing. (FH) Günther Lang, CFDnetwork Engineering Dipl.-Ing. Burkhard Lewerich, CFDnetwork
More informationPIV and LDV measurements behind a backward facing step
PIV and LDV measurements behind a backward facing step M.T. Pilloni, C. Schram, M.L. Riethmulle/^ ^ Mechanical Engineering Department, 09123 Cagliari, Italy ^ von Karman Institute for Fluid Dynamics, 1640
More informationMesh Based Interpolative Coding (MBIC)
Mesh Based Interpolative Coding (MBIC) Eckhart Baum, Joachim Speidel Institut für Nachrichtenübertragung, University of Stuttgart An alternative method to H.6 encoding of moving images at bit rates below
More informationCoE4TN3 Medical Image Processing
CoE4TN3 Medical Image Processing Image Restoration Noise Image sensor might produce noise because of environmental conditions or quality of sensing elements. Interference in the image transmission channel.
More informationFull-Colour, Computational Ghost Video. Miles Padgett Kelvin Chair of Natural Philosophy
Full-Colour, Computational Ghost Video Miles Padgett Kelvin Chair of Natural Philosophy A Quantum Ghost Imager! Generate random photon pairs, illuminate both object and camera SPDC CCD Identical copies
More informationFRED Slit Diffraction Application Note
FRED Slit Diffraction Application Note The classic problem of diffraction through a slit finds one of its chief applications in spectrometers. The wave nature of these phenomena can be modeled quite accurately
More informationFull-field optical methods for mechanical engineering: essential concepts to find one way
Full-field optical methods for mechanical engineering: essential concepts to find one way Yves Surrel Techlab September 2004 1 Contents 1 Introduction 3 2 White light methods 4 2.1 Random encoding............................................
More information