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Proceedings Paper

Neural-net-based explosives recognition with coherent x-ray scatter
Author(s): Joseph Wilder; Alvin Garcia; Stephen M. Wiener
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Paper Abstract

This paper investigates the use of tranform coding and the neural tree network on data obtained from two security systems; face recognition and explosive detection. The use of discrete cosine transform components as features for classification are demonstrated on face recognition data. The use of cepstral components as features for classification are demonstrated for explosive detection on coherent x-ray scattering data, where surrounding materials nonlinearly affect the spectral data obtained from crystalline explosives. The neural tree network is described and shown to be an effective classifier in both applications.

Paper Details

Date Published: 15 September 1995
PDF: 9 pages
Proc. SPIE 2511, Law Enforcement Technologies: Identification Technologies and Traffic Safety, (15 September 1995); doi: 10.1117/12.219588
Show Author Affiliations
Joseph Wilder, Rutgers Univ. (United States)
Alvin Garcia, Rutgers Univ. (United States)
Stephen M. Wiener, Rutgers Univ. (United States)


Published in SPIE Proceedings Vol. 2511:
Law Enforcement Technologies: Identification Technologies and Traffic Safety
Bernard Dubuisson; Geoffrey L. Harding, Editor(s)

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