Algorithm of digital image preprocessing for constructing displacement vector fields

2018 ◽  
Author(s):  
V. V. Titkov ◽  
S. V. Panin ◽  
P. S. Lyubutin ◽  
A. V. Eremin
Keyword(s):  
Digital Image ◽  
Vector Fields ◽  
Displacement Vector ◽  
Image Preprocessing

Micro and Macromechanical Study of Stress-Induced Martensitic Transformation in a Cu-Al-Be Polycrystalline Shape Memory Alloy

2006 ◽  
Vol 509 ◽  
pp. 87-92 ◽  
Author(s):  
F.M. Sánchez ◽  
G. Pulos
Keyword(s):  
Martensitic Transformation ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Vector Fields ◽  
Displacement Vector ◽  
Optical Microscope ◽  
Image Sequences ◽  
Tension Test ◽  
Loading Device ◽  
Stress States

An experimental investigation of the micro and macromechanical stress-induced martensitic transformation in a Cu-Al-Be polycrystalline shape memory alloy is undertaken using a uniaxial tension test. Digital images are acquired at different stress states. The image sequences are analyzed to estimate the optical flow to get displacement vector fields. The experiments are carried out on a miniature hydraulic loading device mounted under an optical microscope. The stress-strain curves and associated images show stress-induced martensitic transformation in specific grains. Displacement vector fields for the polycrystalline shape memory alloy are obtained. They are inhomogeneous due to the martensitic transformation and inter-granular interactions.

scholarly journals Fully Convolutional Network for Consistent Voxel-Wise Correspondence

2020 ◽  
Vol 34 (07) ◽  
pp. 12935-12942 ◽  
Author(s):  
Yungeng Zhang ◽  
Yuru Pei ◽  
Yuke Guo ◽  
Gengyu Ma ◽  
Tianmin Xu ◽  
...  
Keyword(s):  
Vector Fields ◽  
State Of The Art ◽  
Displacement Vector ◽  
Cone Beam Ct ◽  
Deformable Registration ◽  
Cone Beam ◽  
Nonlinear Mapping ◽  
Convolutional Network ◽  
Mapping Functions ◽  
Fully Convolutional Network

In this paper, we propose a fully convolutional network-based dense map from voxels to invertible pair of displacement vector fields regarding a template grid for the consistent voxel-wise correspondence. We parameterize the volumetric mapping using a convolutional network and train it in an unsupervised way by leveraging the spatial transformer to minimize the gap between the warped volumetric image and the template grid. Instead of learning the unidirectional map, we learn the nonlinear mapping functions for both forward and backward transformations. We introduce the combinational inverse constraints for the volumetric one-to-one maps, where the pairwise and triple constraints are utilized to learn the cycle-consistent correspondence maps between volumes. Experiments on both synthetic and clinically captured volumetric cone-beam CT (CBCT) images show that the proposed framework is effective and competitive against state-of-the-art deformable registration techniques.

scholarly journals Crack Propagation Velocity Determination by High-speed Camera Image Sequence Processing

2020 ◽  
Author(s):  
Frank Liebold ◽  
Ali A. Heravi ◽  
Oliver Mosig ◽  
Manfred Curbach ◽  
Viktor Mechtcherine ◽  
...  
Keyword(s):  
Crack Propagation ◽  
High Speed ◽  
Vector Fields ◽  
Displacement Vector ◽  
Image Sequence ◽  
High Speed Camera ◽  
Sequence Processing ◽  
Image Sequence Processing ◽  
Propagation Velocities

The determination of crack propagation velocities can provide valuable information for a better understanding of damage processes of concrete. The spatio-temporal analysis of crack patterns developing at a speed of several hundred meters per second is a rather challenging task. In the paper, a photogrammetric procedure for the determination of crack propagation velocities in concrete specimens using high-speed camera image sequences is presented. A cascaded image sequence processing which starts with the computation of displacement vector fields for a dense pattern of points on the specimen’s surface between consecutive time steps of the image sequence chain has been developed. These surface points are triangulated into a mesh, and as representations of cracks, discontinuities in the displacement vector fields are found by a deformation analysis applied to all triangles of the mesh. Connected components of the deformed triangles are computed using region-growing techniques. Then, the crack tips are determined using principal component analysis. The tips are tracked in the image sequence and the velocities between the time stamps of the images are derived. A major advantage of this method as compared to established techniques is in the fact of its allowing for spatio-temporally resolved, full-field measurements rather than point-wise measurements and that information on crack width can be obtained simultaneously. To validate the experimentation, the authors processed image sequences of tests on four compact-tension specimens performed on a split-Hopkinson tension bar. The images were taken by a high-speed camera at a frame rate of 160,000 images per second. By applying to these datasets the image sequence processing procedure as developed, crack propagation velocities of about 800 m/s were determined with a precision in the order of 50 m/s.

Measurement of displacement vector fields of extended objects

1996 ◽  
Vol 24 (2-3) ◽  
pp. 261-285 ◽  
Author(s):  
Wolfgang Osten ◽  
Werner Jüptner
Keyword(s):  
Vector Fields ◽  
Displacement Vector

Homothetic vector fields in a specially homogenous Bianchi type-I cosmological model in Lyra geometry

2015 ◽  
Vol 93 (11) ◽  
pp. 1397-1401 ◽  
Author(s):  
A.S. Alofi ◽  
Ragab M. Gad
Keyword(s):  
Cosmological Model ◽  
Riemannian Geometry ◽  
Vector Fields ◽  
Bianchi Type ◽  
Displacement Vector ◽  
Lyra Geometry ◽  
Type I ◽  
Bianchi Type I ◽  
Homothetic Vector ◽  
Vector Formula

In this paper, homothetic vector fields of a spatially homogenous Bianchi type-I cosmological model have been evaluated based on Lyra geometry. Further, we investigate the equation of state in cases when a displacement vector [Formula: see text] is a function of t and when it is constant. We give a comparison between the obtained results, using Lyra geometry, and those obtained previously in the context of general relativity, based on Riemannian geometry.

scholarly journals Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study

2021 ◽  
Author(s):  
Salam Dhou ◽  
Mohanad Alkhodari ◽  
Dan Ionascu ◽  
Christopher Williams ◽  
John H. Lewis
Keyword(s):  
Vector Fields ◽  
Displacement Vector ◽  
Cone Beam Ct ◽  
Ground Truth ◽  
Absolute Error ◽  
Tumor Location ◽  
Cone Beam ◽  
Patient Specific ◽  
3D Image ◽  
Motion Models

A method for generating fluoroscopic (time-varying) volumetric images using patient-specific motion models derived from 4-dimensional cone-beam CT (4D-CBCT) images is developed. 4D-CBCT images acquired immediately prior to treatment have the potential to accurately represent patient anatomy and respiration during treatment. Fluoroscopic 3D image estimation is done in two steps: 1) deriving motion models and 2) optimization. To derive motion models, every phase in a 4D-CBCT set is registered to a reference phase chosen from the same set using deformable image registration (DIR). Principal components analysis (PCA) is used to reduce the dimensionality of the displacement vector fields (DVFs) resulting from DIR into a few vectors representing organ motion found in the DVFs. The PCA motion models are optimized iteratively by comparing a cone-beam CT (CBCT) projection to a simulated projection computed from both the motion model and a reference 4D-CBCT phase, resulting in a sequence of fluoroscopic 3D images. Patient datasets were used to evaluate the method by estimating the tumor location in the generated images compared to manually defined ground truth positions. Experimental results showed that the average tumor mean absolute error (MAE) along the superior-inferior (SI) direction and the 95th percentile in two patient datasets were (2.29 mm and 5.79 mm) for patient 1 and (1.89 mm and 4.82 mm) for patient 2. This study has demonstrated the feasibility of deriving 4D-CBCT-based PCA motion models that have the potential to account for the 3D non-rigid patient motion and localize tumors and other patient anatomical structures on the day of treatment.

scholarly journals Quantitative Identification Cracks of Heritage Rock Based on Digital Image Technology

2022 ◽  
Vol 2148 (1) ◽  
pp. 012048
Author(s):  
Xiufang Wang ◽  
Jingyuan Li ◽  
Ming Bai ◽  
Yan Pei
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Rock Fractures ◽  
Processing Technologies ◽  
Image Preprocessing ◽  
Morphological Filtering ◽  
Fracture Area ◽  
Quantitative Identification ◽  
Restoration And Protection

Abstract Digital image processing technologies are used to extract and evaluate the cracks of heritage rock in this paper. Firstly, the image needs to go through a series of image preprocessing operations such as graying, enhancement, filtering and binaryzation to filter out a large part of the noise. Then, in order to achieve the requirements of accurately extracting the crack area, the image is again divided into the crack area and morphological filtering. After evaluation, the obtained fracture area can provide data support for the restoration and protection of heritage rock. In this paper, the cracks of heritage rock are extracted in three different locations.The results show that the three groups of rock fractures have different effects on the rocks, but they all need to be repaired to maintain the appearance of the heritage rock.

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