Analysis of shape recognition capability of Krawtchouk moments

Kaur, Bineet; Joshi, Garima; Vig, Renu

doi:10.1109/ccaa.2015.7148567

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…The Kr-moments are widely used for image processing in various applications like image reconstruction [11], shape recognition [12] and face recognition [13] for their some peculiar characteristics. In particular, since they are discretely defined, they do not involve numerical approximation as in the case of continuous orthogonal moments.…”

Section: Introductionmentioning

confidence: 99%

Micro-Doppler classification of ballistic threats using Krawtchouk moments

Persico

Clemente

Pallotta

et al. 2016

2016 IEEE Radar Conference (RadarConf)

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This version is available at https://strathprints.strath.ac.uk/56501/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Micro-Doppler Classification of Ballistic Threats Using Krawtchouk MomentsAdriano Rosario Persico * , Carmine Clemente * , Luca Pallotta † , Antonio De Maio ‡ and John Soraghan * * University of Strathclyde, CESIP, EEE, 204, George Street, G1 1XW, Glasgow, UK E-mail: adriano.persico, carmine.clemente, j.soraghan-@strath.ac.uk † CNIT, viale G.P. Usberti, n. 181/A -43124 Parma, c/o udr Università "Federico II", via Claudio 21, I-80125 Napoli, Italy. E-mail: luca.pallotta@unina.it. ‡ Università degli Studi di Napoli "Federico II", Dipartimento di Ingegneria Elettrica e delle Tecnologie dellInformazione, Via Claudio 21, I-80125 Napoli, Italy. E-mail: ademaio@unina.it.Abstract-The challenge of ballistic missiles classification is getting greater importance in last years. In fact, since the antimissile defence systems have generally a limited number of interceptors, it is important to distinguish between warheads and confusing objects that the missile releases during its flight, in order to maximize the interception success ratio. For this aim, a novel micro-Doppler based classification technique is presented in this paper characterized by the employment of Krawtchouk moments. Since the evaluation of the latter requires a low computational time, the proposed approach is suitable for real time applications. Finally, a comparison with the 2-dimensional Gabor filter based approach is described by testing both the techniques on real radar data.

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Section: Introductionmentioning

confidence: 99%