Neural-net-based explosives recognition with coherent x-ray scatter

Joseph Wilder; Alvin Garcia; Stephen M. Wiener

doi:10.1117/12.219588

15 September 1995 Neural-net-based explosives recognition with coherent x-ray scatter

Joseph Wilder, Alvin Garcia, Stephen M. Wiener

Proceedings Volume 2511, Law Enforcement Technologies: Identification Technologies and Traffic Safety; (1995) https://doi.org/10.1117/12.219588
Event: European Symposium on Optics for Environmental and Public Safety, 1995, Munich, Germany

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.

Citation Download Citation

Joseph Wilder, Alvin Garcia, and Stephen M. Wiener "Neural-net-based explosives recognition with coherent x-ray scatter", Proc. SPIE 2511, Law Enforcement Technologies: Identification Technologies and Traffic Safety, (15 September 1995); https://doi.org/10.1117/12.219588

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