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Proceedings Paper

Pattern recognition of industrial defects by multiresolution analysis with wavelet decomposition
Author(s): Denis Deguillemont; Stephane Lecoeuche; Jean-Paul Dubus
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Paper Abstract

The purpose of this paper is to present a method of pattern recognition applied to detect discrimination in objects manufactured in plastic, metal, glass... This discrimination is needed to avoid problems during the recycling process. Nowadays, the controls are realized by an operator who checks visually these objects. As in texture segmentation, a way to limit the data which much be analyzed, is to use orthogonal transformations. In an industrial background, one of the most interesting transformations is the orthogonal wavelet decomposition. Remaining in the image vector space, this decomposition allows a multi resolution analysis and keeps quite all the original information in the subimages. Applied to industrial objects presenting a complex textured aspect, all the wavelets (Haar, bi-orthogonal...) need post- processing to display the defects. As these defects are seen like texture breakdowns, they can be located in high frequency spatial domain. This has led us to choose Daubechies wavelets that concentrate correctly the useful information in the detail subimages. We show that the defect is more clearly apparent at a given resolution level than in the original image. We give criteria that allow the determination of this optimal resolution level. We present a method that allows the reconstruction of the defect, using the subimages. The defect, appearing on a black background, is then discriminated by an adapted classical pattern recognition method.

Paper Details

Date Published: 19 October 1998
PDF: 11 pages
Proc. SPIE 3458, Wavelet Applications in Signal and Imaging Processing VI, (19 October 1998); doi: 10.1117/12.328138
Show Author Affiliations
Denis Deguillemont, Ecole d'Ingenieurs du Pas-de-Calais (France)
Stephane Lecoeuche, Ecole d'Ingenieurs du Pas-de-Calais (France)
Jean-Paul Dubus, Univ. des Sciences et Technologies de Lille (France)


Published in SPIE Proceedings Vol. 3458:
Wavelet Applications in Signal and Imaging Processing VI
Andrew F. Laine; Michael A. Unser; Akram Aldroubi, Editor(s)

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