Dr. Martin A. Hunt Profile

Dr. Martin A. Hunt

Director of Applications Engineering at Coherent Logix Inc

SPIE Involvement:

Author

Proceedings Article | 27 May 2011 Paper

Parallel design patterns for a low-power, software-defined compressed video encoder

Michael Bruns, Martin Hunt, Durga Prasad, Nageswara Gunupudi, Sekar Sonachalam

Proceedings Volume 8063, 80630E (2011) https://doi.org/10.1117/12.884422

KEYWORDS: Computer programming, Data modeling, Video, Parallel processing, Video compression, Parallel computing, Clocks, Quantization, Computer architecture, Video acceleration

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Proceedings Article | 5 May 2011 Paper

Low-power, real-time digital video stabilization using the HyperX parallel processor

Martin Hunt, Lin Tong, Keith Bindloss, Shang Zhong, Steve Lim, Benjamin Schmid, J. Tidwell, Paul Willson

Proceedings Volume 8050, 80501T (2011) https://doi.org/10.1117/12.884390

KEYWORDS: Video, Cameras, Video processing, Sensors, Computer programming, Video surveillance, Corner detection, Image filtering, Motion measurement, Parallel computing

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Proceedings Article | 15 July 2003 Paper

Semiconductor wafer defect detection using digital holography

Mark Schulze, Martin Hunt, Edgar Voelkl, Joel Hickson, William Usry, Randall Smith, Robert Bryant, C. Thomas

Proceedings Volume 5041, (2003) https://doi.org/10.1117/12.485237

KEYWORDS: Digital holography, Semiconducting wafers, Defect detection, Inspection, Scanning electron microscopy, Visualization, Holograms, Wavefronts, Digital imaging, Image visualization

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Proceedings Article | 22 May 2003 Paper

Automated image registration in semiconductor industry: a case study in the direct-to-digital holography inspection system

X. Dai, Martin Hunt

Proceedings Volume 5011, (2003) https://doi.org/10.1117/12.479688

KEYWORDS: Image registration, Semiconducting wafers, Fourier transforms, Optical alignment, Wafer inspection, Holograms, Defect detection, Semiconductors, Inspection, Wavefronts

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Proceedings Article | 12 July 2002 Paper

Direct to digital holography for semiconductor wafer defect detection and review

C. Thomas, Tracy Bahm, Larry Baylor, Philip Bingham, Steven Burns, Matt Chidley, Long Dai, Robert Delahanty, Christopher Doti, Ayman El-Khashab, Robert Fisher, Judd Gilbert, James Goddard, Gregory Hanson, Joel Hickson, Martin Hunt, Kathy Hylton, George John, Michael Jones, Ken Macdonald, Michael Mayo, Ian McMackin, Dave Patek, John Price, David Rasmussen, Louis Schaefer, Thomas Scheidt, Mark Schulze, Philip Schumaker, Bichuan Shen, Randall Smith, Allen Su, Kenneth Tobin, William Usry, Edgar Voelkl, Karsten Weber, Paul Jones, Robert Owen

Proceedings Volume 4692, (2002) https://doi.org/10.1117/12.475659

KEYWORDS: Holograms, Digital holography, Holography, Semiconducting wafers, Cameras, Deep ultraviolet, Spatial frequencies, Beam splitters, Digital video recorders, Fourier transforms

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Proceedings Article | 2 June 2000 Paper

Paradigm for selecting the optimum classifier in semiconductor automatic defect classification applications

Martin Hunt, James Goddard, James Mullens, Regina Ferrell, Bobby Whitus, Ariel Ben-Porath

Proceedings Volume 3998, (2000) https://doi.org/10.1117/12.386481

KEYWORDS: Semiconductors, Scanning electron microscopy, Neural networks, Semiconducting wafers, Defect detection, Electron microscopes, Manufacturing, Classification systems, Very large scale integration, Inspection

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The automatic classification of defects found on semiconductor wafers using a scanning electron microscope (SEM) is a complex task that involves many steps. The process includes re- detecting the defect, measuring attributes of the defect, and automatically assigning a classification. In many cases, especially during product ramp-up, and when multiple products are manufactured in the same line, there are few training examples for an automatic defect classification (ADC) system. This condition presents a problem for traditional supervised parametric and nonparametric learning techniques. In this paper we investigate the attributes of several approaches to ADC and compare their performance under a variety of available training data scenarios. We have selected to characterize the attributes and performance of a traditional K-nearest neighbor classifier, probabilistic neural network (PNN), and rule-based classifier in the context of SEM ADC. The PNN classifier is a nonparametric supervised classifier that is built around a radial basis function (RBF) neural network architecture. A basic summary of the PNN will be presented along with the generic strengths and weakness described in the literature and observed with actual semiconductor defect data. The PNN classifier is able to manage conditions such as non-convex class distributions and single class multiple clusters in feature space. A rule-based classifier producing built-in core classes provided by the Applied Materials SEMVision tool will be characterized in the context of both few examples and no examples. An extensive set of fab generated data is used to characterize the performance of these ADC approaches. Typical data sets contain from 30 to greater than 200. The number of classes in the data set range from 4 to more than 12. The conclusions reached from this analysis indicate that the strengths of each method are evident under specific conditions that are related to different stages within the VLSI yield curve, and to the number of different products in the line.

Proceedings Article | 21 March 2000 Paper

Accommodating multiple illumination sources in an imaging colorimetry environment

Kenneth Tobin, James Goddard, Martin Hunt, Kathy Hylton, Thomas Karnowski, Marc Simpson, Roger Richards, Dale Treece

Proceedings Volume 3966, (2000) https://doi.org/10.1117/12.380073

KEYWORDS: Metals, Spectroscopy, Image processing, Image segmentation, Imaging systems, Manufacturing, Spectrophotometry, Color difference, Colorimetry, Inspection

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Proceedings Article | 26 August 1999 Paper

Facet model and mathematical morphology for surface characterization

Besma Abidi, Hamed Sari-Sarraf, James Goddard, Martin Hunt

Proceedings Volume 3837, (1999) https://doi.org/10.1117/12.360312

KEYWORDS: Image segmentation, Image processing, Image processing algorithms and systems, Algorithm development, Image filtering, Mathematical modeling, Mathematical morphology, CCD cameras, Detection and tracking algorithms, Image enhancement

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Proceedings Article | 8 March 1999 Paper

Depth measurement of moving slurry at the wet end of a paper machine

James Goddard, Hamed Sari-Sarraf, John Turner, Martin Hunt, Besma Abidi

Proceedings Volume 3652, (1999) https://doi.org/10.1117/12.341149

KEYWORDS: Cameras, Image processing, Imaging systems, Sensors, Light sources and illumination, Binary data, CMOS cameras, Process control, High speed cameras, Computing systems

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Proceedings Article | 8 March 1999 Paper

Imaging tristimulus colorimeter for the evaluation of color in printed textiles

Martin Hunt, James Goddard, Kathy Hylton, Thomas Karnowski, Roger Richards, Marc Simpson, Kenneth Tobin, Dale Treece

Proceedings Volume 3652, (1999) https://doi.org/10.1117/12.341131

KEYWORDS: Image segmentation, Imaging systems, Optical filters, Image processing, Cameras, Reflectivity, Image processing algorithms and systems, CCD cameras, Prototyping, Spectrophotometry

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Proceedings Article | 3 April 1997 Paper

Circumference imaging for optical-based identification of cylindrical and conical objects

Martin Hunt, David Sitter, Regina Ferrell, J. Eric Breeding

Proceedings Volume 3028, (1997) https://doi.org/10.1117/12.270351

KEYWORDS: Cameras, Image processing, Distortion, Imaging systems, Image sensors, Sensors, Image acquisition, Line scan image sensors, Image segmentation, Lamps

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Proceedings Article | 21 February 1996 Paper

Part identification using robust feature extraction and pattern classification

Martin Hunt, J. Steve Hicks, Shaun Gleason

Proceedings Volume 2665, (1996) https://doi.org/10.1117/12.232243

KEYWORDS: Hough transforms, Image classification, Image processing, Feature extraction, Image enhancement, Mahalanobis distance, Artillery, Image segmentation, Computing systems, Image acquisition

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SPIE Journal Paper | 1 April 1991

Moment invariants for automated inspection of printed material

Marc Simpson, Richard Schmoyer, Martin Hunt

OE, Vol. 30, Issue 04, (April 1991) https://doi.org/10.1117/12.10.1117/12.55813

KEYWORDS: Inspection, Visualization, Mahalanobis distance, Halftones, Image processing, Pattern recognition, Image segmentation, Reflectivity, Printing, Digital imaging

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Proceedings Article | 1 March 1991 Paper

Subpixel measurement of image features based on paraboloid surface fit

Shaun Gleason, Martin Hunt, William Jatko

Proceedings Volume 1386, (1991) https://doi.org/10.1117/12.25387

KEYWORDS: Machine vision, System integration, Algorithm development, Inspection, Data modeling, Image processing, Image registration, 3D modeling, Visualization, Distance measurement

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Proceedings Article | 1 September 1990 Paper

Nonlinear filter derived from topological image features

William Jatko, Martin Hunt, Kenneth Tobin

Proceedings Volume 1295, (1990) https://doi.org/10.1117/12.21217

KEYWORDS: Image filtering, Printing, Image processing, Image registration, Inspection, Laser engraving, Nonlinear filtering, Error analysis, Statistical analysis, Algorithm development

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