Abstract
In this paper we approach the problem of fast surface grading of flat pieces decorated with random patterns. The proposed method is based on the use of global statistics of color computed in the CIE Lab space. Two other fast methods based on color histograms [1] and Centile-LBP features [8] are introduced for comparison purposes. We used CIE Lab in order to provide accuracy and perceptual approach in color difference computation. Experiments with RGB were also carried out to study CIE Lab reliability. The ground truth was provided through an image database of ceramic tiles. Nevertheless, the approach is suitable to be extended to other random decorated surfaces like marble, granite, wood or textile stuff. The experiments make us to conclude that a simple collection of global statistics of color in the CIE Lab space is powerful enough to well discriminate surface grades. The average success surpasses 95% in most of the tests, improving literature methods and achieving factory compliance.
Partially supported by FEDER-CICYT(DPI2003-09173-C02-01) and Keraben S.A.
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© 2005 Springer-Verlag Berlin Heidelberg
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López, F., Valiente, J.M., Baldrich, R., Vanrell, M. (2005). Fast Surface Grading Using Color Statistics in the CIE Lab Space. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_81
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DOI: https://doi.org/10.1007/11492542_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
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