Dr. Matthew J. Harker Profile

Dr. Matthew J. Harker

Ph.D Student at Montan Univ Leoben

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Publications (9)

Proceedings Article | 30 April 2015 Paper

MATLAB toolbox for the regularized surface reconstruction from gradients

Matthew Harker, Paul O'Leary

Proceedings Volume 9534, 95341E (2015) https://doi.org/10.1117/12.2182827

KEYWORDS: Reconstruction algorithms, MATLAB, Matrices, Inverse problems, Numerical analysis, Pollution control, Machine vision, Current controlled current source, Algorithm development, Dysprosium

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Proceedings Article | 6 March 2013 Paper

Machine vision system for the control of tunnel boring machines

Michael Habacher, Paul O'Leary, Matthew Harker, Johannes Golser

Proceedings Volume 8661, 86610G (2013) https://doi.org/10.1117/12.2003847

KEYWORDS: Control systems, Cameras, Machine vision, Imaging systems, Light emitting diodes, Detection and tracking algorithms, Image quality, Binary data, Image processing, Dysprosium

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Proceedings Article | 6 March 2013 Paper

Structural deformation measurement via efficient tensor polynomial calibrated electro-active glass targets

Christoph Gugg, Matthew Harker, Paul O'Leary

Proceedings Volume 8661, 86610F (2013) https://doi.org/10.1117/12.2003679

KEYWORDS: Calibration, Glasses, Distortion, Cameras, Lenses, Opacity, Measurement devices, Matrices, Mathematical modeling, Electroluminescent displays

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This paper describes the physical setup and mathematical modelling of a device for the measurement of structural deformations over large scales, e.g., a mining shaft. Image processing techniques are used to determine the deformation by measuring the position of a target relative to a reference laser beam. A particular novelty is the incorporation of electro-active glass; the polymer dispersion liquid crystal shutters enable the simultaneous calibration of any number of consecutive measurement units without manual intervention, i.e., the process is fully automatic. It is necessary to compensate for optical distortion if high accuracy is to be achieved in a compact hardware design where lenses with short focal lengths are used. Wide-angle lenses exhibit significant distortion, which are typically characterized using Zernike polynomials. Radial distortion models assume that the lens is rotationally symmetric; such models are insufficient in the application at hand. This paper presents a new coordinate mapping procedure based on a tensor product of discrete orthogonal polynomials. Both lens distortion and the projection are compensated by a single linear transformation. Once calibrated, to acquire the measurement data, it is necessary to localize a single laser spot in the image. For this purpose, complete interpolation and rectification of the image is not required; hence, we have developed a new hierarchical approach based on a quad-tree subdivision. Cross-validation tests verify the validity, demonstrating that the proposed method accurately models both the optical distortion as well as the projection. The achievable accuracy is e ≤ ±0.01 [mm] in a field of view of 150 [mm] x 150 [mm] at a distance of the laser source of 120 [m]. Finally, a Kolmogorov Smirnov test shows that the error distribution in localizing a laser spot is Gaussian. Consequently, due to the linearity of the proposed method, this also applies for the algorithm's output. Therefore, first-order covariance propagation provides an accurate estimate of the measurement uncertainty, which is essential for any measurement device.

Proceedings Article | 2 February 2012 Paper

Strain analysis by regularized non-rigid registration

Amir Badshah, Paul O'Leary, Matthew Harker, Daniel Tscharnuter

Proceedings Volume 8300, 83000D (2012) https://doi.org/10.1117/12.920003

KEYWORDS: Image registration, Strain analysis, Stochastic processes, Composites, Coating, Distortion, Image compression, Optical testing, Stress analysis, Astatine

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Proceedings Article | 12 July 2011 Paper

Non-rigid registration for qualitiy control of printed materials

Amir Badshah, Paul O'Leary, Matthew Harker, Christian Sallinger

Proceedings Volume 8000, 80000J (2011) https://doi.org/10.1117/12.890901

KEYWORDS: Image registration, Image filtering, Partial differential equations, Data acquisition, MATLAB, Linear filtering, Matrices, Automatic control, Error analysis, Image restoration

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Proceedings Article | 7 February 2011 Paper

Gram polynomial image decimation and its application to non-rigid registration

Amir Badshah, Paul O'Leary, Matthew Harker

Proceedings Volume 7877, 787707 (2011) https://doi.org/10.1117/12.876665

KEYWORDS: Image registration, Signal to noise ratio, Image restoration, Distortion, Smoothing, Biomedical optics, Feature extraction, Gaussian filters, Image processing, Clouds

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SPIE Journal Paper | 1 July 2010

Discrete polynomial moments and the extraction of 3-D embossed digits for recognition

Paul O'Leary, Matthew Harker, Bernhard Mörtl

JEI, Vol. 19, Issue 3, 031205, (July 2010) https://doi.org/10.1117/12.10.1117/1.3455988

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SPIE Journal Paper | 1 January 2009

Discrete polynomial moments for real-time geometric surface inspection

Paul O'Leary, Matthew Harker

JEI, Vol. 18, Issue 01, 013015, (January 2009) https://doi.org/10.1117/12.10.1117/1.2987725

KEYWORDS: Inspection, Condition numbers, Error analysis, Copper, Data modeling, Matrices, Data acquisition, Stochastic processes, Visual process modeling, Image processing

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Proceedings Article | 11 March 2005 Paper

Incremental matrix orthogonalization with an application to curve fitting

Matthew Harker, Paul O'Leary, Paul Zsombor-Murray

Proceedings Volume 5674, (2005) https://doi.org/10.1117/12.586499

KEYWORDS: Tolerancing, Space operations, Matrices, Quality measurement, Computational imaging, Electronic imaging, Silicon, Condition numbers, Clouds, Numerical stability

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Showing 5 of 9 publications

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