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Proceedings Paper

Lighting inhomogeneities removal by wavelet analysis
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Paper Abstract

Lighting uniformity is always an issue in visual inspection of industrial parts. While the human visual system is quite able to cope with this kind of problem, artificial vision systems are subject to false and no detection rate increase when the lighting conditions are not well mastered. If many authors have proposed various methods to unbiase image, most of the time they are designed in an "ad hoc" way and they are very dependent on the experimental conditions. It can be shown that a large class of the inhomogeneities in images due to lighting conditions can be reasonably modelled by a polynomial dependency of the luminance. The wavelet analysis theory proposes a lot of bases with various number of vanishing moments. By keeping only some wavelet coeffcients it is possible to reconstruct an unbiased signal in which the interesting features, characterized by there resolution pertinence range, are cleaned from the polynomial variations supposed to be due to inhomogeneous lighting conditions. In this paper, after a brief presentation of a realistic lighting model, we show that the luminance image can be approximated by a polynomial function. Then we propose a method, based on a partial reconstruction after multiresolution analysis, allowing to remove approximately the polynomial component of the signal. Two variants are also proposed to improve the performance by either detecting more precisely the polynomial component, either limiting the error occurring when neglecting the approximation signal in the reconstruction process. A simulation in 1D and 2D illustrates these propositions. Some results obtained on examples of real artificial vision inspection problems are finally given.

Paper Details

Date Published: 19 October 2006
PDF: 12 pages
Proc. SPIE 6383, Wavelet Applications in Industrial Processing IV, 638304 (19 October 2006); doi: 10.1117/12.687939
Show Author Affiliations
O. Laligant, Le2i, CNRS, Univ. de Bourgogne (France)
F. Mériaudeau, Le2i, CNRS, Univ. de Bourgogne (France)
F. Truchetet, Le2i, CNRS, Univ. de Bourgogne (France)

Published in SPIE Proceedings Vol. 6383:
Wavelet Applications in Industrial Processing IV
Frédéric Truchetet; Olivier Laligant, Editor(s)

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