Projection registration applied to nondestructive testing

Bingham, Philip R.; Arrowood, Lloyd

doi:10.1117/1.3489122

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Over the past decades, various image registration methods have been proposed. Among the existing methods, the transform-based method [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], feature-based method [24,25], and others. The term "transform-based methods" is used here in a global sense.…”

Section: Introductionmentioning

confidence: 99%

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Advancements in 2D/3D Image Registration Methods

2023

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In this paper, we present methods for identifying an image from a given set of Radon projections. Given a suitably regular 2-D or 3-D function, we form a new function 𝑔 from 𝑓 using a linear transformation. We show how the Radon projections of 𝑓 and 𝑔 can be used to determine the transformation. The proposed algorithms introduce three major contributions, (1) Improvements on the 2-D setting using the moments of the Radon projections with only two orthogonal projections. (2) A natural extension of the 2-D setting to work with the 3-D setting. In particular, reducing the 3-D problem to a 2-D problem so that we can recover a translation, a scaling, or a rotation transformation of a 3-D object in the Radon domain. (3) An efficient method of recovering a rotation of a 3-D image around an arbitrary axis and an angle of rotation.

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Section: Introductionmentioning

confidence: 99%

“…Direct implementation in Radon domain is presented in [6][7][8]. The Fourier phase matching method [9] is applied on the registration of radiography and computed tomography projections. In [10] the authors use the results obtained in [6] to identify the transform parameters for a fast-matching algorithm.…”

Section: Introductionmentioning

confidence: 99%

Advancements in 2D/3D Image Registration Methods

2023

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“…1,2 Generally, the most important task of industrial CT imaging is to detect the defects (e.g., cracks and pores) of the inspected object. 1,2 Generally, the most important task of industrial CT imaging is to detect the defects (e.g., cracks and pores) of the inspected object.…”

Section: Introductionmentioning

confidence: 99%

Improved total variation-based image reconstruction algorithm for linear scan cone-beam computed tomography

Zeng

Liu

2013

J. Electron. Imaging

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Linear scan cone-beam computed tomography (LSCBCT) is a technically simple computed tomography (CT) configuration and is powerful enough to inspect long objects. As one kind of limitedangle problem, the image reconstruction of LSCBCT is ill posed. However, the total variation minimization (TVM)-projection on convex sets (POCS) reconstruction algorithm, which is based on the TVM and POCS, has been proven effective for solving the limited-angle problem. While applying the TVM-POCS algorithm to the LSCBCT reconstruction, the reconstructed image is distorted near the edges of the object. To solve this problem, an improved iterative reconstruction algorithm was developed. The improved method integrated simultaneous algebraic reconstruction technique, TVM, and C-V model. The C-V model can detect objects whose boundaries are not necessarily defined by gradient. The developed algorithm can reduce artifacts by piecewise constant modification and get a more accurate image. Numerical simulations are presented to illustrate the effectiveness of the algorithm. Moreover, the developed algorithm can be applied to other x-ray CT reconstruction problems.

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Estimation of affine transformations directly from tomographic projections in two and three dimensions

Mooser

Forsberg

Hack

et al. 2011

Machine Vision and Applications

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This paper presents a new approach to estimate two-and three-dimensional affine transformations from tomographic projections. Instead of estimating the deformation from the reconstructed data, we introduce a method which works directly in the projection domain, using parallel and fan beam projection geometries. We show that any affine deformation can be analytically compensated, and we develop an efficient multiscale estimation framework based on the normalized cross correlation. The accuracy of the approach is verified using simulated and experimental data, and we demonstrate that the new method needs less projection angles and has a much lower computational complexity as compared to approaches based on the standard reconstruction techniques.

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Projection registration applied to nondestructive testing

Cited by 4 publications

References 8 publications

Advancements in 2D/3D Image Registration Methods

Advancements in 2D/3D Image Registration Methods

Improved total variation-based image reconstruction algorithm for linear scan cone-beam computed tomography

Estimation of affine transformations directly from tomographic projections in two and three dimensions

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