Image segmentation for the application of the neugebauer colour prediction model on inkjet printed ceramic tiles

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Abstract

Colour prediction models (CPM) can be used to analyze the printing quality of halftone-based color printing systems. In this paper, we consider the Neugebauer CPM which requires as input the fraction of occupation of each primary. To obtain these numbers, we apply several image segmentation algorithms, with and without contextual information. These segmentation algorithms are evaluated with respect to another technique based on mixtures of factor analyzers. More importantly, the segmentation results are evaluated with respect to the performance of the Neugebauer CPM when used with the obtained fractions of occupation. This evaluation is carried out by comparing the predicted color against that measured with a spectrophotometer, and testifies for the adequacy of the approach. © Springer-Verlag Berlin Heidelberg 2005.

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Latorre, P., Peris-Fajarnes, G., & Figueiredo, M. A. T. (2005). Image segmentation for the application of the neugebauer colour prediction model on inkjet printed ceramic tiles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3656 LNCS, pp. 9–16). https://doi.org/10.1007/11559573_2

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