Abstract
We present a soft computing techniques based option for assessing the quality of colour prints. The values of several print distortion attributes are evaluated by employing data clustering, support vector regression, and image analysis procedures and then aggregated into an overall print quality measure using fuzzy integration. The experimental investigations performed have shown that the print quality evaluations provided by the measure correlate well with the print quality rankings obtained from the experts. The developed tools are successfully used in a printing shop for routine print quality control.
We gratefully acknowledge the support we have received from the Foundation for Knowledge and Competence Development, Sweden.
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Verikas, A., Bacauskiene, M., Nilsson, CM. (2006). Soft Computing for Assessing the Quality of Colour Prints. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_76
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DOI: https://doi.org/10.1007/11779568_76
Publisher Name: Springer, Berlin, Heidelberg
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