Genetic Algorithms for Training Data and Polynomial Optimization in Colorimetric Characterization of Scanners
Generalization is an important issue in colorimetric characterization of devices. We propose a framework based on Genetic Algorithms to select training samples from large datasets. Even though the framework is general, and can be used in principle for any dataset, we use two well known datasets as case studies: training samples are selected from the Macbeth ColorCheckerDC dataset and the trained models are tested on the Kodak Q60 photographic standard dataset. The presented experimental results show that the proposed framework has better, or at least comparable, performances than a set of other computational methods defined so far for the same goal (Hardeberg, Cheung, CIC and Schettini). Even more importantly, the proposed framework has the ability to optimize the training samples and the characterizing polynomial’s coefficients at the same time.
KeywordsGenetic Algorithm Training Sample Degree Polynomial Color Patch Polynomial Optimization
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- 1.Bianco, S., Gasparini, F., Schettini, R., Vanneschi, L.: An evolutionary framework for colorimetric characterization of scanners. In: Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Drechsler, R., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., McCormack, J., O’Neill, M., Romero, J., Rothlauf, F., Squillero, G., Uyar, A.Ş., Yang, S. (eds.) EvoWorkshops 2008. LNCS, vol. 4974, pp. 245–254. Springer, Heidelberg (2008)CrossRefGoogle Scholar
- 3.Cheung, T.L., Westland, S.: Color selections for characterization charts. In: Proceedings of the Second European Conference on Colour in Graphics, Imaging and Vision, Aachen, Germany, pp. 116–119 (2004)Google Scholar
- 6.Chou, Y., Li, C., Luo, M.: A new colour selection method for characterising digital cameras. In: Proceedings of the 17th Color Imaging Conference (2009) (to appear)Google Scholar
- 8.Hardeberg, J.Y., Brettel, H., Schmitt, F.J.M.: Spectral characterization of electronic cameras. In: Electronic Imaging: Processing, Printing, and Publishing in Color. SPIE, Zurich (1998)Google Scholar
- 9.Holland, J.H.: Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)Google Scholar
- 10.Huffel, S., Vandewalle, J.: The total least squares problem: computational aspects and analysis. Society for Industrial and Applied Mathematics, Philadelphia (1991)Google Scholar
- 11.Kang, H.: Computational coolor technology, vol. PM159. SPIE Press (2006)Google Scholar
- 12.Pellegri, P., Novati, G., Schettini, R.: Training set selection for multispectral imaging systems characterization. Journal of Imaging Science and Technology 48(3), 203–210 (2004)Google Scholar