Mr. Anh H. Trang Profile

Anh H. Trang

Electronics Engineer at US Army CCDC C5ISR Ctr Night Vision & Electronic Sensors Directorate

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Author

Publications (26)

Proceedings Article | 23 May 2011 Paper

Validating spectral spatial detection based on MMPP formulation

Anh Trang, Sanjeev Agarwal, Thomas Broach, Thomas Smith

Proceedings Volume 8017, 801723 (2011) https://doi.org/10.1117/12.886804

KEYWORDS: Land mines, Target detection, Detection and tracking algorithms, Algorithm development, Mining, Statistical analysis, Device simulation, Expectation maximization algorithms, Detector development, Computer simulations

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Spectral, shape or texture features of the detected targets are used to model the likelihood of the targets to be potential mines in a minefield. However, some potential mines can be false alarms due to the similarity of the mine signatures with natural and other manmade clutter signatures. Therefore, in addition to the target features, spatial distribution of the detected targets can be used to improve the minefield detection performance. In our recently published SPIE paper, we evaluated minefield detection performance for both patterned and unpatterned minefields in highly cluttered environments, simultaneously using both target features and target spatial distributions that define Markov Marked Point Process (MMPP). The results have suggested that proper exploitation of spectral/shape features and spatial distributions can indeed contribute improved performance of patterned and unpatterned minefield detection. Also, the ability of the algorithm to detect the minefields in highly cluttered environments shows the robustness of the developed minefield detection algorithm based on MMPP formulation. Moreover, the results show that the MMPP minefield detection algorithm performs significantly better than the baseline algorithm employing spatial point process with false alarm mitigation. Since these results were based on the simulated data, it is not clear that the MMPP detection algorithm has fully achieved its best performance. To validate its performance, an analytical solution for the minefield detection problem will be developed, and its performance will be compared with the performance of the simulated solution. The analytical solution for the complete minefield detection problem is intractable due to a large number of detections and the variation of the number of detected mines in the minefield process. Therefore, an analytical solution for a simplified detection problem will be derived, and its minefield performance will be compared with the minefield performance obtained from the simulation in the same MMPP framework for different clutter rates.

Proceedings Article | 29 April 2010 Paper

Exploiting spatial distributions for minefield detection in cluttered environment

Anh Trang, Sanjeev Agarwal, Thomas Broach, Thomas Smith

Proceedings Volume 7664, 766426 (2010) https://doi.org/10.1117/12.851488

KEYWORDS: Land mines, Detection and tracking algorithms, Target detection, Algorithm development, Mining, Environmental sensing, Evolutionary algorithms, Sensors, Detector development, Computer simulations

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Proceedings Article | 5 May 2009 Paper

Collection and evaluation of false alarm signatures in background data

Sanjeev Agarwal, Shivakar Vulli, Neil Malloy, Elizabeth Lord, Josh Fairley, Bruce Sabol, Wesley Johnson, Richard Ess, Anh Trang

Proceedings Volume 7303, 730318 (2009) https://doi.org/10.1117/12.819498

KEYWORDS: Multispectral imaging, Mining, Databases, Mid-IR, Vegetation, Sensors, Land mines, Infrared signatures, Infrared imaging, Target detection

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Proceedings Article | 5 May 2009 Paper

Simultaneously exploiting spectral similarity and spatial distribution for patterned minefield detection

Anh Trang, Sanjeev Agarwal, Thomas Broach, Thomas Smith

Proceedings Volume 7303, 73032B (2009) https://doi.org/10.1117/12.819336

KEYWORDS: Land mines, Target detection, Expectation maximization algorithms, Detection and tracking algorithms, Mining, Sensors, Algorithm development, Fermium, Frequency modulation, Computer simulations

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Proceedings Article | 5 May 2009 Paper

Spectral and spatial analysis of false alarms in background data

Abhishek Sanaka, Shivakar Vulli, Sanjeev Agarwal, Richard Ess, Anh Trang

Proceedings Volume 7303, 730316 (2009) https://doi.org/10.1117/12.819501

KEYWORDS: Vegetation, Near infrared, Land mines, Multispectral imaging, Mid-IR, Sensors, Spatial analysis, Algorithm development, Mining, Target detection

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Proceedings Article | 29 April 2008 Paper

Exploiting "mineness" for scatterable minefield detection

Anh Trang, Sanjeev Agarwal, Thomas Broach, Thomas Smith

Proceedings Volume 6953, 695317 (2008) https://doi.org/10.1117/12.779585

KEYWORDS: Land mines, Target detection, Mining, Fermium, Frequency modulation, Sensors, Expectation maximization algorithms, Detection and tracking algorithms, Algorithm development, Computer simulations

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Proceedings Article | 29 April 2008 Paper

Comparative performance between compressed and uncompressed airborne imagery

Chung Phan, Ronald Rupp, Sanjeev Agarwal, Anh Trang, Sumesh Nair

Proceedings Volume 6953, 69530U (2008) https://doi.org/10.1117/12.782360

KEYWORDS: Image compression, Land mines, Detection and tracking algorithms, Algorithms, Target detection, Mining, Data compression, Sensors, Image quality, Unmanned aerial vehicles

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Proceedings Article | 29 April 2008 Paper

FastKRX: a fast approximation for kernel RX anomaly detection

Spandan Tiwari, Sanjeev Agarwal, Anh Trang

Proceedings Volume 6953, 695316 (2008) https://doi.org/10.1117/12.779586

KEYWORDS: Sensors, Land mines, Explosives, Target detection, Lawrencium, Detection and tracking algorithms

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Proceedings Article | 29 April 2008 Paper

HAMD: a software system for surface and buried mine detections

Bo Ling, Ming Liu, Uma Venkataraman, Anh Trang

Proceedings Volume 6953, 695318 (2008) https://doi.org/10.1117/12.780369

KEYWORDS: Land mines, Image segmentation, Mining, Detection and tracking algorithms, Image enhancement, Vegetation, Image processing algorithms and systems, Image fusion, Sensors, Algorithm development

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Proceedings Article | 7 May 2007 Paper

A patterned and un-patterned minefield detection in cluttered environments using Markov marked point process

Anh Trang, Sanjeev Agarwal, Phillip Regalia, Thomas Broach, Thomas Smith

Proceedings Volume 6553, 655313 (2007) https://doi.org/10.1117/12.721368

KEYWORDS: Land mines, Target detection, Mining, Environmental sensing, Sensors, Metals, Detection and tracking algorithms, Data modeling, Data analysis, Image processing

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Proceedings Article | 27 April 2007 Paper

Buried mine detection in airborne imagery using co-occurrence texture features

Spandan Tiwari, Sanjeev Agarwal, Anh Trang

Proceedings Volume 6553, 65530Z (2007) https://doi.org/10.1117/12.721509

KEYWORDS: Mining, Land mines, Sensors, Matrices, Feature extraction, Multispectral imaging, Statistical analysis, Infrared signatures, Feature selection, Target detection

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Proceedings Article | 26 April 2007 Paper

Multi-classifier buried mine detection using MWIR images

Bo Ling, Anh Trang, Chung Phan

Proceedings Volume 6553, 655310 (2007) https://doi.org/10.1117/12.720857

KEYWORDS: Mining, Mid-IR, Land mines, Image fusion, Target detection, Image processing, Feature extraction, Sensors, Wavelets, Infrared signatures

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Proceedings Article | 18 May 2006 Paper

Design tradeoffs for an airborne minefield detection system

Saurabh Agarwal, Sanjeev Agarwal, Ron Rupp, Anh Trang

Proceedings Volume 6217, 62173E (2006) https://doi.org/10.1117/12.673806

KEYWORDS: Land mines, Sensors, Target detection, Detection and tracking algorithms, Unmanned aerial vehicles, Statistical analysis, Image segmentation, Device simulation, Data modeling, Mining

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Proceedings Article | 16 May 2006 Paper

Surface and buried mine detection using MWIR images

Bo Ling, Sushanth Dabbiru, Anh Trang, Chung Phan

Proceedings Volume 6217, 62170F (2006) https://doi.org/10.1117/12.665730

KEYWORDS: Mining, Land mines, Mid-IR, Wavelets, Sensors, Detection and tracking algorithms, Image processing, Metals, Image processing algorithms and systems, Discrete wavelet transforms

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Proceedings Article | 10 June 2005 Paper

Warfighter-in-the-loop: mental models in airborne minefield detection

Madhu Reddy, Sanjeev Agarwal, Richard Hall, John Brown, Thomas Woodard, Anh Trang

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.604789

KEYWORDS: Land mines, Sensors, Zoom lenses, Interfaces, Mining, Performance modeling, Cognitive modeling, Automatic target recognition, Human-machine interfaces, Target detection

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Proceedings Article | 10 June 2005 Paper

Phenomenology of dynamic thermal signatures around surface mines

M. Albert, G. Koh, G. Koenig, S. Howington, J. Peters, A. Trang

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.603559

KEYWORDS: Mining, Land mines, Thermography, Temperature metrology, Infrared imaging, Infrared signatures, Soil science, Meteorology, Infrared radiation, Infrared cameras

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Proceedings Article | 10 June 2005 Paper

Evaluating operator performance in aided airborne mine detection

Sanjeev Agarwal, Madhu Reddy, Richard Hall, Thomas Woodard, John Brown, Anh Trang

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.604675

KEYWORDS: Land mines, Mining, Sensors, Target detection, Mid-IR, Human subjects, Automatic target recognition, Visual process modeling, Human-machine interfaces, Interfaces

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In this paper we evaluate mine level detection performance of the human operator using high resolution mid-wave infrared (MWIR) imagery and compare it with the performance of automatic target recognition (ATR) like RX detector. Previous studies have shown that the anomaly detectors like the RX detector and even more sophisticated ATR techniques fall short of the performance achieved by human analyst for mine and minefield detection. There are three main objectives of the paper. First, we seek to establish performance bounds for mine detection using a single MWIR sensor under different conditions. Second, we evaluate the conditions under which the human visual system contributes significantly over and above RX anomaly detector. Third, we seek to qualitatively study the visual processes and mental models employed by the human operators to detect mines. A graphical user interface (HILgui) was developed using MATLAB to evaluate mine level detection performance for the operator. This interface is used to conduct a series of experiments examining performance for twenty subjects. The mine images varied systematically based on the time of day the images were collected, the type of terrain and type of mines. All the experiments were video-recorded and post-experiment interviews were conducted for qualitative analysis. Both qualitative and quantitative research techniques were used to gather and analyze the data. Results from different quantitative analysis including the accuracy of mine detection, propensity of false alarms and the time taken by the operator to mark individual targets are discussed. The mental models developed by the subjects for detection of mine targets are also discussed. Limitations of the current experiments and plans for future work are discussed. It is hoped that this systematic evaluation of a human operator in airborne mine detection will help in developing new and better ATR techniques and help identify critical features required in the operator interface for the warfighter-in-the-loop (WIL) minefield detection.

Proceedings Article | 10 June 2005 Paper

Semi-automated based ground-truthing GUI for airborne imagery

Chung Phan, Rich Lydic, Tim Moore, Anh Trang, Sanjeev Agarwal, Spandan Tiwari

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.605208

KEYWORDS: Image processing, Target detection, Airborne remote sensing, Algorithm development, Detection and tracking algorithms, Sensors, Land mines, Mining, MATLAB, Human-machine interfaces

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Proceedings Article | 21 September 2004 Paper

Image-based synthesis of airborne minefield MWIR data

Sanjeev Agarwal, Thandava Edara, C. Swonger, Anh Trang

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.546045

KEYWORDS: Land mines, Mid-IR, Algorithm development, Databases, Detection and tracking algorithms, Image quality, Mathematical modeling, Sensors, Data modeling, Magnetorheological finishing

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Proceedings Article | 21 September 2004 Paper

Temperature measurements and high-resolution IR images of mines at an arid site

Anh Trang, Brian Baertlein

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.541332

KEYWORDS: Mining, Land mines, Cameras, Temperature metrology, Infrared imaging, Sensors, Vegetation, Thermography, Infrared cameras, Soil science

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Proceedings Article | 22 August 2000 Paper

Extended Kalman filtering and fixed interval smoothing for the vehicle-mounted mine/UXO detector system

Anh Trang

Proceedings Volume 4038, (2000) https://doi.org/10.1117/12.396177

KEYWORDS: Filtering (signal processing), Electronic filtering, Sensors, Land mines, Mining, Detection and tracking algorithms, Algorithm development, Signal processing, Forward looking infrared, Metals

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Proceedings Article | 4 September 1998 Paper

Identification of metallic mines using low-frequency magnetic fields

Lloyd Riggs, Jonathan Mooney, Daniel Lawrence, J. Thomas Broach, Anh Trang

Proceedings Volume 3392, (1998) https://doi.org/10.1117/12.324233

KEYWORDS: Signal to noise ratio, Magnetism, Aluminum, Data modeling, Mining, Monte Carlo methods, Detection and tracking algorithms, Sensors, Error analysis, Metals

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Proceedings Article | 4 September 1998 Paper

Kalman filtering for target (mine) tracking in the presence of antenna motion

Anh Trang

Proceedings Volume 3392, (1998) https://doi.org/10.1117/12.324148

KEYWORDS: Filtering (signal processing), Mining, Electronic filtering, Detection and tracking algorithms, Receivers, Signal detection, Target detection, Antennas, Radar, Land mines

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Proceedings Article | 22 July 1997 Paper

Characterization of small metallic objects and nonmetallic antipersonnel mines

Anh Trang, Peter Czipott, Deborah Waldron

Proceedings Volume 3079, (1997) https://doi.org/10.1117/12.280863

KEYWORDS: Sensors, Head, Magnetism, Metals, Receivers, Mining, Target detection, Transmitters, Land mines, Copper

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Proceedings Article | 31 May 1996 Paper

Simulation of mine detection over dry soil, snow, ice, and water

Anh Trang

Proceedings Volume 2765, (1996) https://doi.org/10.1117/12.241246

KEYWORDS: Land mines, Mining, Signal attenuation, Explosives, Soil science, Data modeling, Aluminum, Antennas, Wave propagation, Radio propagation

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Proceedings Article | 20 June 1995 Paper

Advanced mine detection radar

Anh Trang

Proceedings Volume 2496, (1995) https://doi.org/10.1117/12.211371

KEYWORDS: Target detection, Radar, Land mines, Data processing, Mining, Advanced radar, System identification, Sun, Data acquisition, Signal processing

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Showing 5 of 26 publications

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