Dr. Bruce N. Nelson Profile

Dr. Bruce N. Nelson

Principal Scientist at Battenkill Technologies Inc

SPIE Involvement:

Author

Proceedings Article | 28 March 2005 Paper

Effect of algorithm fusion and aggregation methodologies on the performance of a corrosion detection algorithm

Bruce Nelson, Paul Slebodnick, William Groeninger, Edward Lemieux

Proceedings Volume 5813, (2005) https://doi.org/10.1117/12.603948

KEYWORDS: Detection and tracking algorithms, Image fusion, Corrosion, Inspection, Image filtering, Edge detection, Algorithm development, Image analysis, Wavelets, Binary data

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Proceedings Article | 12 April 2004 Paper

Automated development of linguistic-fuzzy classifier membership functions and weights for use in disparate sensor integration visible and infrared imaging sensor classification

Bruce Nelson, Amnon Birenzvige

Proceedings Volume 5434, (2004) https://doi.org/10.1117/12.540858

KEYWORDS: Sensors, Infrared sensors, Cameras, Visible radiation, Imaging systems, Infrared imaging, Image sensors, Optical sensors, Information fusion, Video

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In support of the Disparate Sensor Integration (DSI) Program a number of imaging sensors were fielded to determine the feasibility of using information from these systems to discriminate between chemical and conventional munitions. The camera systems recorded video from 160 training and 100 blind munitions detonation events. Two types of munitions were used; 155 mm conventional rounds and 155 mm chemical simulant rounds. In addition two different modes of detonation were used with these two classes of munitions; detonation on impact (point detonation) and detonation in the air (airblasts). The cameras fielded included two visible wavelength cameras, a near infrared camera (peak responsivity of approximately 1μm), a mid wavelength infrared camera system (3 μm to 5 μm) and a long wavelength infrared camera system (7.5 μm to 13 μm). Our recent work has involved developing Linguistic-Fuzzy Classifiers for performing munitions detonation classification with the DSI visible and infrared imaging sensors data sets. In this initial work, the classifiers were heuristically developed based on analyses of the training data features distributions. In these initial classification systems both the membership functions and the feature weights were hand developed and tuned. We have recently developed new methodologies to automatically generate membership functions and weights in Linguistic-Fuzzy Classifiers. This paper will describe this new methodology and provide an example of its efficacy for separating munitions detonation events into either air or point detonation. This is a critical initial step in achieving the overall goal of DSI; the classification of detonation events as either chemical or conventional. Further, the detonation mode is important as it significantly effects the dispersion of agents. The results presented in this paper clearly demonstrate that the automatically developed classifiers perform as well in this classification task as the previously developed and demonstrated empirically developed classifiers.

Proceedings Article | 12 April 2004 Paper

Fusion of color, grayscale, and edge-detection algorithms for the accurate assessment of corrosion in shipboard tank and void imagery

Bruce Nelson, Paul Slebodnick, William Groeninger, Edward Lemieux

Proceedings Volume 5434, (2004) https://doi.org/10.1117/12.540920

KEYWORDS: Corrosion, Image fusion, Inspection, Detection and tracking algorithms, Image analysis, Analytical research, Algorithm development, Video

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Proceedings Article | 1 April 2003 Paper

CB detection and early warning--fusing disparate sensors into the detection process: program overview

Amnon Birenzvige, David Sickenberger, Felix Reyes, William Underwood, Christian Reiff, David Gonski, Monique Fargues, Bruce Nelson

Proceedings Volume 5099, (2003) https://doi.org/10.1117/12.497980

KEYWORDS: Sensors, Artillery, Situational awareness sensors, Acoustics, Biological detection systems, Information fusion, Detection and tracking algorithms, Roads, Cameras, Computer intrusion detection

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Improved situational awareness is a primary goal for the Objective Force. Knowing where the enemy is and what are the threats to his troops provides the commander with the information he needs to plan his mission and provide his forces with maximum protection from the variety of threats that are present on the battlefield. Sensors play an important role in providing critical information to enhance situational awareness. The sensors that are used on the battlefield include, among others, seismic, acoustic, and cameras in different spectral ranges of the electro-magnetic spectrum. These sensors help track enemy movement and serve as part of an intrusion detection system. Characteristically these sensors are relatively cheap and easy to deploy. Chemical and biological agent detection is currently relegated to sensors that are specifically designed to detect these agents. Many of these sensors are collocated with the troops. By the time alarm is sounded the troops have already been exposed to the agent. In addition, battlefield contaminants frequently interfere with the performance of these sensors and result in false alarms. Since operating in a contaminated environment requires the troops to don protective garments that interfere with their performance we need to reduce false alarms to an absolute minimum. The Edgewood Chemical and Biological Center (ECBC) is currently conducting a study to examine the possibility of detecting chemical and biological weapons as soon as they are deployed. For that purpose we conducted a field test in which the acoustic, seismic and electro-magnetic signatures of conventional and simulated chemical / biological artillery 155mm artillery shells were recorded by an array of corresponding sensors. Initial examination of the data shows a distinct differences in the signatures of these weapons. In this paper we will provide detailed description of the test procedures. We will describe the various sensors used and describe the differences in the signatures generated by the conventional and the (simulated) chemical rounds. This paper will be followed by other papers that will provide more details information gained by the various sensors and describe how fusing the data enhance the reliability of the CB detection process.

Proceedings Article | 1 April 2003 Paper

Multiple algorithm fusion in a corrosion detection algorithm used with shipboard tank and void inspection systems

Bruce Nelson, Paul Slebodnick, Edward Lemieux

Proceedings Volume 5099, (2003) https://doi.org/10.1117/12.496912

KEYWORDS: Detection and tracking algorithms, Inspection, Corrosion, Image analysis, Video, Calibration, Image fusion, Information fusion, Analytical research, Video processing

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Proceedings Article | 1 April 2003 Paper

CB round discrimination fusing visible and infrared camera data

Bruce Nelson, Amnon Birenzvige, William Underwood, David Sickenberger

Proceedings Volume 5099, (2003) https://doi.org/10.1117/12.499294

KEYWORDS: Cameras, Visible radiation, Imaging systems, Infrared cameras, Optical sensors, Long wavelength infrared, Video, Feature extraction, Explosives, Lithium

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In support of the Disparate Sensor Integration (DSI) Program a number of imaging sensors were fielded to determine the feasibility of using information from these systems to discriminate between chemical simulant and high explosives munitions. The imaging systems recorded video from 160 training and 100 blind munitions detonation events. Two types of munitions were used; 155 mm high explosives rounds and 155 mm chemical simulant rounds. In addition two different modes of detonation were used with these two classes of munitions; detonation on impact (point detonation) and detonation prior to impact (airblasts). The imaging sensors fielded included two visible wavelength cameras, a near infrared camera, a mid wavelength infrared camera system and a long wavelength infrared camera system. Our work to date has concentrated on using the data from one of the visible wavelength camera systems and the long wavelength infrared camera system. The results provided in this paper clearly show the potential for discriminating between the two types of munitions and the two detonation modes using these camera data. It is expected that improved classification robustness will be achieved when the camera data described in this paper is combined with results and discriminating features generated from some of the other camera systems as well as the acoustic and seismic sensors also fielded in support of the DSI Program. The paper will provide a brief description of the camera systems and provide still imagery that show the four classes of explosives events at the same point in the munitions detonation sequence in both the visible and long wavelength infrared camera data. Next the methods used to identify frames of interest from the overall video sequence will be described in detail. This will be followed by descriptions of the features that are extracted from the frames of interest. A description of the system that is currently used for performing classification with the extracted features and the results attained on the blind test data set are next described. The work performed to date to fuse information from the visible and long wavelength infrared imaging sensors including the benefits realized are next described. The paper concludes with a description of our ongoing work to fuse imaging sensor data.

Proceedings Article | 6 March 2002 Paper

Generation and fusion of multiple image representations in automatic corrosion detection algorithms used with shipboard tank video inspection systems

Bruce Nelson, Paul Slebodnick, Edward Lemieux, Matt Krupa, Robert Preisser, Keith Lucas

Proceedings Volume 4731, (2002) https://doi.org/10.1117/12.458375

KEYWORDS: Inspection, Corrosion, Detection and tracking algorithms, Video, Image fusion, Algorithm development, Binary data, Image analysis, Cameras, Imaging systems

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Proceedings Article | 26 March 2001 Paper

Wavelet processing for image denoising and edge detection in automatic corrosion detection algorithms used in shipboard ballast tank video inspection systems

Bruce Nelson, Paul Slebodnick, Edward Lemieux, William Singleton, Matt Krupa, Keith Lucas, E. Thomas, Andrew Seelinger

Proceedings Volume 4391, (2001) https://doi.org/10.1117/12.421194

KEYWORDS: Corrosion, Inspection, Video, Wavelets, Detection and tracking algorithms, Cameras, Edge detection, Imaging systems, Digital video recorders, Binary data

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Proceedings Article | 17 August 2000 Paper

Automatic vehicle detection in infrared imagery using a novel method for defining regions of interest, feature extraction, and a fuzzy logic classification system

Bruce Nelson

Proceedings Volume 4050, (2000) https://doi.org/10.1117/12.395555

KEYWORDS: Fuzzy systems, Infrared radiation, Infrared imaging, Fuzzy logic, Feature extraction, Binary data, Classification systems, Infrared sensors, Missiles, Infrared detectors

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Proceedings Article | 2 August 1999 Paper

Fuzzy set information fusion in land mine detection

Bruce Nelson, Paul Gader, James Keller

Proceedings Volume 3710, (1999) https://doi.org/10.1117/12.356997

KEYWORDS: Calibration, Automatic target recognition, Information fusion, Mining, Fuzzy systems, Sensors, Land mines, Fuzzy logic, Radar, Data centers

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Proceedings Article | 2 August 1999 Paper

New results in fuzzy-set-based detection of land mines with GPR

Paul Gader, Hichem Frigui, Bruce Nelson, Gary Vaillette, James Keller

Proceedings Volume 3710, (1999) https://doi.org/10.1117/12.356988

KEYWORDS: Land mines, Mining, General packet radio service, Ground penetrating radar, Analytical research, Calibration, Prototyping, Fuzzy logic, Feature extraction, Palladium

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Proceedings Article | 26 November 1996 Paper

Demonstration of a VOC in-situ fiber optic sensor for use with a penetrometer analysis system

Steven Hartenstein, Glenn Moore, Bruce Nelson, James Kane, Mark Lowe

Proceedings Volume 2835, (1996) https://doi.org/10.1117/12.259764

KEYWORDS: Sensors, Fiber optics sensors, Luminescence, Crystals, Analytical research, Fiber optics, Quartz, Optical components, Fiber optic components, Sensing systems

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Proceedings Article | 1 March 1992 Paper

Chemical sensors for environmental monitoring

Mary Tabacco, Quan Zhou, Bruce Nelson

Proceedings Volume 1587, (1992) https://doi.org/10.1117/12.56553

KEYWORDS: Sensors, Fiber optics sensors, Glasses, Polymers, Chemical fiber sensors, Fiber optics, Environmental monitoring, Environmental sensing, Polymeric sensors, Humidity

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Showing 5 of 13 publications

Conference Committee Involvement (4)

Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2006

19 April 2006 | Orlando (Kissimmee), Florida, United States

Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005

30 March 2005 | Orlando, Florida, United States

Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2004

14 April 2004 | Orlando, Florida, United States

Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications

23 April 2003 | Orlando, Florida, United States

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