NDLI: Automatic threat object classification based on extracted features from electromagnetic imaging system

Content Provider	IEEE Xplore Digital Library
Author	Al-Qubaa, A.R. Tian, G.Y.
Copyright Year	2012
Description	Author affiliation: School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK (Al-Qubaa, A.R.; Tian, G.Y.)
Abstract	The detection of concealed weapons is one of the biggest challenges facing homeland security. It has been shown that each weapon can have a unique fingerprint, which is an electromagnetic signal determined by its size, shape, and physical composition. Extracting the signature of each weapon is one of the major tasks of any detection system. In this paper, feature extraction of a new metal detector signal is conducted using a Wavelet and Fourier Transform. These features are used to classify two different groups of threat objects. Artificial Neural Network (ANN) and Support Vector Machines (SVM) classification techniques are used to classify the metal objects towards automatic threat object detection and classification. Promising classification accuracy rates are obtained from using individual and combined features.
Starting Page	164
Ending Page	169
File Size	931887
Page Count	6
File Format	PDF
ISBN	9781457717765
e-ISBN	9781457717758
DOI	10.1109/IST.2012.6295536
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-16
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Artificial neural networks Weapons Support vector machine classification Imaging Metals
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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