Higher order based image deconvolution in electromagnetic non destructive evaluation of metallic materials

Authors:
Pietro Burrascano;Matteo Cacciola;Francesco Carlo Morabito;Marco Ricci
Affiliations:
University of Perugia, Polo Scientifico e Didattico di Terni, Strada Pentima Bassa n. 4, 05100 Terni, Italy: E-mail: {marco.ricci, pietro.burrascano}@unipg.it;University Mediterranea of Reggio Calabria, DIMET, Via Graziella Feo di Vito, 89100 Reggio Calabria, Italy/ E-mail: {matteo.cacciola, morabito}@unirc.it;University Mediterranea of Reggio Calabria, DIMET, Via Graziella Feo di Vito, 89100 Reggio Calabria, Italy/ E-mail: {matteo.cacciola, morabito}@unirc.it;University of Perugia, Polo Scientifico e Didattico di Terni, Strada Pentima Bassa n. 4, 05100 Terni, Italy: E-mail: {marco.ricci, pietro.burrascano}@unipg.it
Venue:
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
Year:
2011

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Abstract

We present a non-destructive magnetic imaging technique developed for the evaluation of hot-rolled stainless steel. Starting from measurements of magnetic field carried out by means of a Hall probe array, magnetic images of sample surfaces are attained. In order to enhance the signal to noise ratio and to detect defects, we have implemented some image processing protocols. In particular we report the contextual application of Independent Component Analysis and Wiener filter to the image deconvolution task focusing on the advantages that such approach assures.