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Gun detection and classification based on feature extraction from a new sensor array imaging system

Lookup NU author(s): Abdalrahman Al-Qubaa, Abeer Al-Shiha, Professor Gui Yun TianORCiD


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© 2013 IEEE.Electromagnetic imaging currently occupies a vital role in various disciplines from engineering to medical applications. These roles are based upon the fundamentals of Electromagnetic (EM) fields and their relationship with the material properties under evaluation. A new system based on a Giant Magneto-Resistive (GMR) sensor array was built to capture the scattered EM signal returned by metallic objects. This paper evaluates the capabilities of the new system based on features extracted from objects response to EM fields. A novel amplitude variation feature is proposed to obtain high classification rates. The selected features of metallic objects are applied to detect and classify 'threat' items. A collection of handguns with other commonly used metallic objects are tested. Promising results show that the new system can detect and identify the threat items. This novel procedure has the potential to produce significant improvements in automatic weapon detection and classification.

Publication metadata

Author(s): Al-Qubaa AR, Al-Shiha A, Tian GY

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 2013 International Conference on Electrical, Communication, Computer, Power, and Control Engineering (ICECCPCE 2013)

Year of Conference: 2013

Pages: 88-94

Online publication date: 29/12/2014

Acceptance date: 01/01/1900

Publisher: IEEE


DOI: 10.1109/ICECCPCE.2013.6998740

Library holdings: Search Newcastle University Library for this item

ISBN: 9781479956333