Mr. John M. Trenkle Profile

John M. Trenkle

at Michigan Aerospace Corp

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Author

Publications (9)

Proceedings Article | 30 May 2006 Paper

3D sensor algorithms for spacecraft pose determination

John Trenkle, Peter Tchoryk, Greg Ritter, Jane Pavlich, Aaron Hickerson

Proceedings Volume 6220, 62200D (2006) https://doi.org/10.1117/12.669260

KEYWORDS: Sensors, Data modeling, 3D modeling, Space operations, 3D acquisition, Solid modeling, Algorithm development, Satellites, Image processing, Detection and tracking algorithms

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Researchers at the Michigan Aerospace Corporation have developed accurate and robust 3-D algorithms for pose determination (position and orientation) of satellites as part of an on-going effort supporting autonomous rendezvous, docking and space situational awareness activities. 3-D range data from a LAser Detection And Ranging (LADAR) sensor is the expected input; however, the approach is unique in that the algorithms are designed to be sensor independent. Parameterized inputs allow the algorithms to be readily adapted to any sensor of opportunity. The cornerstone of our approach is the ability to simulate realistic range data that may be tailored to the specifications of any sensor. We were able to modify an open-source raytracing package to produce point cloud information from which high-fidelity simulated range images are generated. The assumptions made in our experimentation are as follows: 1) we have access to a CAD model of the target including information about the surface scattering and reflection characteristics of the components; 2) the satellite of interest may appear at any 3-D attitude; 3) the target is not necessarily rigid, but does have a limited number of configurations; and, 4) the target is not obscured in any way and is the only object in the field of view of the sensor. Our pose estimation approach then involves rendering a large number of exemplars (100k to 5M), extracting 2-D (silhouette- and projection-based) and 3-D (surface-based) features, and then training ensembles of decision trees to predict: a) the 4-D regions on a unit hypersphere into which the unit quaternion that represents the vehicle [Q_X, Q_Y, Q_Z, Q_W] is pointing, and, b) the components of that unit quaternion. Results have been quite promising and the tools and simulation environment developed for this application may also be applied to non-cooperative spacecraft operations, Autonomous Hazard Detection and Avoidance (AHDA) for landing craft, terrain mapping, vehicle guidance, path planning and obstacle avoidance.

Proceedings Article | 18 September 1997 Paper

Determination of bake time and temperature of painted plastic using mathematical morphology and neural networks

Robert Lougheed, Michelle Mikulec, John Trenkle, David McCubbrey

Proceedings Volume 3205, (1997) https://doi.org/10.1117/12.285584

KEYWORDS: Mathematical morphology, Neural networks, Image processing, Image analysis, Inspection

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Proceedings Article | 14 November 1996 Paper

Mosaic construction, processing, and review of very large electron micrograph composites

Robert Vogt, John Trenkle, Laurel Harmon

Proceedings Volume 2847, (1996) https://doi.org/10.1117/12.258213

KEYWORDS: Axons, Image processing, Image registration, Composites, Nerve, Image resolution, Photomicroscopy, Biopsy, Tissues, Electron microscopy

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Proceedings Article | 7 March 1996 Paper

Word-level recognition of multifont Arabic text using a feature vector matching approach

Erik Erlandson, John Trenkle, Robert Vogt

Proceedings Volume 2660, (1996) https://doi.org/10.1117/12.234725

KEYWORDS: Image segmentation, Databases, Image quality, Optical character recognition, Computing systems, Binary data, Data modeling, Systems modeling, Image resolution, Feature extraction

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Proceedings Article | 23 March 1994 Paper

Disambiguation and spelling correction for a neural network based character recognition system

John Trenkle, Robert Vogt

Proceedings Volume 2181, (1994) https://doi.org/10.1117/12.171120

KEYWORDS: Optical character recognition, Neural networks, Detection and tracking algorithms, Image segmentation, Feature extraction, Logic, Binary data, System identification, Image processing, Associative arrays

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Proceedings Article | 25 February 1994 Paper

Region-of-interest detection for fingerprint classification

John Trenkle

Proceedings Volume 2103, (1994) https://doi.org/10.1117/12.169478

KEYWORDS: Binary data, Convolution, Neural networks, Image processing, Feature extraction, Image classification, Databases, Detection and tracking algorithms, Image segmentation, Classification systems

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Proceedings Article | 13 April 1993 Paper

Feature set optimization for the recognition of Arabic characters using genetic algorithms

Steven Schlosser, John Trenkle, Robert Vogt

Proceedings Volume 1838, (1993) https://doi.org/10.1117/12.142800

KEYWORDS: Genetic algorithms, Genetics, Machine vision, Computer vision technology, Optimization (mathematics), Binary data, Classification systems, Optical character recognition, Feature extraction, Prototyping

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Proceedings Article | 13 April 1993 Paper

Database representation for scene simulation

Laurel Harmon, Charles Cole, John Trenkle, Steven Schlosser, D. Luczkiewicz, K. Piech

Proceedings Volume 1838, (1993) https://doi.org/10.1117/12.142797

KEYWORDS: Databases, Data modeling, 3D modeling, Cameras, Visual process modeling, Machine vision, Computer vision technology, Electro optical modeling, Sensors, Buildings

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Proceedings Article | 1 July 1991 Paper

Morphological feature-set optimization using the genetic algorithm

John Trenkle, Steven Schlosser, Robert Vogt

Proceedings Volume 1568, (1991) https://doi.org/10.1117/12.46117

KEYWORDS: Genetic algorithms, Genetics, Image processing, Binary data, Distance measurement, Optimization (mathematics), Optical character recognition, Classification systems, Feature extraction, Image segmentation

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Showing 5 of 9 publications

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