Dr. Hanna Tran Haskett Profile

Dr. Hanna Tran Haskett

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

SPIE Involvement:

Author

Publications (12)

Proceedings Article | 13 August 2002 Paper

Statistical analysis of polarization responses for land mines in various solar angles and backgrounds using airborne laser imagery

Hanna Haskett, Ronald Rupp

Proceedings Volume 4742, (2002) https://doi.org/10.1117/12.479068

KEYWORDS: Mining, Polarization, Land mines, Sun, Airborne laser technology, Sensors, Statistical analysis, Image registration, Databases, Data analysis

Read Abstract +

Proceedings Article | 13 August 2002 Paper

Land mine performance bounds in various background using airborne 808 nm laser imagery

Hanna Haskett, Ronald Rupp

Proceedings Volume 4742, (2002) https://doi.org/10.1117/12.479059

KEYWORDS: Land mines, Mining, Detection and tracking algorithms, Palladium, Dubnium, Tantalum, Terbium, Sensors, Airborne laser technology, Target detection

Read Abstract +

Proceedings Article | 22 October 2001 Paper

Complexity of confidence level optimization in sequential automatic target detection of hyperspectral system

Hanna Haskett, Arun Sood, Mohammad Habib

Proceedings Volume 4379, (2001) https://doi.org/10.1117/12.445387

KEYWORDS: Palladium, Image resolution, Target detection, Detection and tracking algorithms, Image processing, Automatic target recognition, Sensors, Binary data, Fermium, Frequency modulation

Read Abstract +

Proceedings Article | 18 October 2001 Paper

Surface mine detection in the 3- to 5-um band using neural networks

Thomas Donzelli, Hanna Haskett

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445483

KEYWORDS: Mining, Neural networks, Land mines, Neurons, Image processing, Palladium, Mid-IR, Sensors, Target detection, Cameras

Read Abstract +

Proceedings Article | 18 October 2001 Paper

Detectability of buried mines in 3- to 5-um and 8-to 12-um regions for various soils using hyperspectral signatures

Hanna Haskett, Donald Reago, Ronald Rupp

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445481

KEYWORDS: Mining, Distance measurement, Roads, Land mines, Soil science, Vegetation, Palladium, Sensors, Statistical analysis, Data analysis

Read Abstract +

Proceedings Article | 18 October 2001 Paper

Minefield performance for LAMD using AMBER broadband/multiband MWIR imagery

Hanna Haskett, Thomas Donzelli

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445478

KEYWORDS: Land mines, Mining, Detection and tracking algorithms, Target detection, Sensors, Algorithm development, Mid-IR, Palladium, Automatic target recognition, Statistical analysis

Read Abstract +

This paper includes analysis/assessment and development of detection algorithms: (1) the assessment of detectability of surface mines using the RX algorithm implementation, which in turn, provides a first look at the limitation of the algorithm for suitable real-time implementation; (2) the development of the adaptive real-time mine detection algorithm (ARMD) based on statistical analysis of the data. The statistical analysis includes the class distribution between mines and background, the underlying distribution for mines and background based on the quantile-quantile plot. The paper also compares the quantitative performance of probability of detection (Pd) and false alarm rates (FAR) for different detection techniques for different background and mine types. This paper also presents the minefield probability of detection versus minefield false alarm rate to gauge the minefield detection performance trade-off using: (1) only mine density; and (2) mine density with pattern. This paper also demonstrates the importance of the observables that offer the class separability between mine/target and background for automatic target detection/recognition applications. Detection algorithms with high computational capability are not the 'silver bullet' for automatic target detection/recognition as commonly believed. The art of ATR is the ability to be able to pinpoint the observables that distinguish mines and background. Once the observables offer the class separability between classes are established, any simple correlation method can deliver an acceptable performance (demonstrating that highly computational methods, indeed, are wasteful and unnecessary). This paper uses the multiband and broadband data collected with the AMBER (3.5-5)mum) camera in May 2000. This data set contains about 513 (approximately 1.1 in resolution) images covering three spectral regions: 3-5)mum, 3- 4.2)mua and 4.2-5)mua. The total number of mines and the area coverage for these three spectral regions are approximately 579, and 25200m², respectively. Note that each spectral region contains 171 images (of which 53 images contain mines with 131 large mines, and 62 small mines) covering about 8400m². Also note that to stimulate minefields, an image containing 3 mines with a straight line pattern is defined as a minefield opportunity.

Proceedings Article | 18 October 2001 Paper

Identification of optimal bands in the 3- to 5-um region for lightweight airborne mine detection (LAMD) system

Hanna Haskett, Donald Reago, Richard Legault

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445477

KEYWORDS: Land mines, Sensors, Mining, FT-IR spectroscopy, Fourier transforms, Infrared signatures, Signal attenuation, Infrared spectroscopy, Spectroscopy, Databases

Read Abstract +

Proceedings Article | 22 August 2000 Paper

Mine detection performance by fusing ground-penetrating radars and metal detector

Hanna Haskett, J. Thomas Broach

Proceedings Volume 4038, (2000) https://doi.org/10.1117/12.396311

KEYWORDS: Sensors, General packet radio service, Metals, Land mines, Palladium, Mining, Ground penetrating radar, Data fusion, Gallium, Infrared sensors

Read Abstract +

Proceedings Article | 22 August 2000 Paper

Quantitative performance of buried mine hyperspectral reflectance signatures (0.35-2.5 um) in various soils

Hanna Haskett, Ronald Rupp, Tim Moore

Proceedings Volume 4038, (2000) https://doi.org/10.1117/12.396316

KEYWORDS: Mining, Distance measurement, Land mines, Soil science, Roads, Vegetation, Reflectivity, Palladium, Statistical analysis, Sensors

Read Abstract +

Proceedings Article | 24 August 1999 Paper

Hyperspectral target detection using sequential approach

Hanna Haskett, Arun Sood, Mohammad Habib

Proceedings Volume 3718, (1999) https://doi.org/10.1117/12.359989

KEYWORDS: Palladium, Detection and tracking algorithms, Phase modulation, Image processing, Sensors, Computing systems, Hyperspectral target detection, Databases, Visible radiation, Near infrared

Read Abstract +

Proceedings Article | 2 August 1999 Paper

Automatic mine detection algorithm using ground penetration radar signatures

Hanna Haskett, J. Thomas Broach

Proceedings Volume 3710, (1999) https://doi.org/10.1117/12.357114

KEYWORDS: Mining, Radar, Land mines, Sensors, Databases, Detection and tracking algorithms, Ground penetrating radar, Algorithm development, Target detection, Fourier transforms

Read Abstract +

Proceedings Article | 2 July 1998 Paper

Trade-off studies of detection performance versus the number of reflective spectral bands in hyperspectral imagery

Hanna Haskett, Arun Sood

Proceedings Volume 3372, (1998) https://doi.org/10.1117/12.312606

KEYWORDS: Target detection, Image processing, Detection and tracking algorithms, Hyperspectral imaging, Sensors, Reflectivity, Palladium, Imaging systems, Optical filters, Roads

Read Abstract +

Showing 5 of 12 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years