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An Empirical Approach for Spectral Color Printers Characterization

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The spectral-based characterization of inkjet printers is often based on a physical description of the printing process. The objective of our work is to see whether an approach based on the use of neural networks is an effective strategy for spectral printer characterization without requiring a deep knowledge of the printing process. In our experiments, we treat the printers as RGB devices, and exploit finite-dimensional linear models to reduce the amount of information required to characterize them. To select a good architecture, we compared the behavior of 15 different networks to compute reflectance spectra from RGB digital counts. To test our characterization procedure we consider an Epson 890 inkjet printer using photo quality paper.
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Document Type: Research Article

Publication date: January 1, 2004

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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