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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References
Boukouvalas, C., et al.: Color grading of randomly textured ceramic tiles using color histograms. IEEE Trans. Industrial Electronics. 46(1), 219–226 (1999)
Boukouvalas, C., Petrou, M.: Perceptual correction for colour grading using sensor transformations and metameric Data. Machine Vision and Applications 11, 96–104 (1998)
Boukouvalas, C., Petrou, M.: Perceptual correction for colour grading of random textures. Machine Vision and Appl. 12, 129–136 (2000)
Baldrich, R., Vanrell, M., Villanueva, J.J.: Texture-color features for tile classification. In: EUROPTO/SPIE Conf. on Color and Polarisation Techniques in Indust. Inspection, Germany (1999)
Lumbreras, F., et al.: Color texture recognition through multiresolution features. In: Int. Conf. on Quality Control by Artificial Vision, France, vol. 1, pp. 114–121 (2001)
Peñaranda, J.A., Briones, L., Florez, J.: Color machine vision system for process control in ceramics industry. In: SPIE, vol. 3101, pp. 182–192 (1997)
Kauppinen, H.: Development of a color machine vision method for wood surface inspection. Phd Thesis, Oulu University (1999)
Kyllönen, J., Pietikäinen, M.: Visual inspection of parquet slabs by combining color and texture. In: Proc. IAPR Workshop on Machine Vision Appl., Japan,(2000)
Lebrun, V., Macaire, L.: Aspect inspection of marble tiles by color line-scan camera. In: Int. Conf. on Quality Control by Artificial Vision, France (2001)
Kukkonen, S., Kvnen, H., Parkkinen, J.: Color Features for Quality Control in Ceramic Tile Industry. Optical Engineering 40(2), 170–177 (2001)
Duda, R.O., Hart, P.E.: Pattern classification and scene analysis. John Wiley and Sons, New York (1973)
Wyszecki, G., Stiles, W.S.: Color sciencie: concepts and methods, quantitative data and formulae, 2nd edn. Wiley, New York (1982)
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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
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