Paper
28 July 1997 Enhancement and fusion of data for concealed weapon detection
Mohamed-Adel Slamani, Liane C. Ramac, Mucahit K. Uner, Pramod K. Varshney, Donald D. Weiner, Mark G. Alford, David D. Ferris Jr., Vincent C. Vannicola
Author Affiliations +
Abstract
A wide variety of concealed weapon detection systems are being investigated to determine the potential payoffs of employing these sensors to detect weapons concealed under a person's clothing. The enabling sensing mechanisms being studied include infrared, acoustic, millimeter wave, and X- ray sensors. The primary emphasis of this paper is on infrared. A new technique for processing sensor data by partitioning non-homogeneous images into homogeneous regions for later detection and identification processing is presented. The name of this method is Automated Statistical Characterization and Partitioning of Environments (A'SCAPE). A'SCAPE enables image enhancement for reliable detection and identification of weapons concealed under varying layers of clothing through its mapping process. By employing a variety of sensors, another enabling technology for concealed weapon detection (CWD) is sensor fusion. Concepts for experiments and analysis are discussed to determine the feasibility of sensor fusion approaches for CWD.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohamed-Adel Slamani, Liane C. Ramac, Mucahit K. Uner, Pramod K. Varshney, Donald D. Weiner, Mark G. Alford, David D. Ferris Jr., and Vincent C. Vannicola "Enhancement and fusion of data for concealed weapon detection", Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, (28 July 1997); https://doi.org/10.1117/12.280804
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Cited by 18 scholarly publications.
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KEYWORDS
Weapons

Image fusion

Sensors

Infrared sensors

Composites

Data fusion

Image processing

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