Investigating the Possibility of Using Fewer Training Samples: In the Color Prediction Model based on CIEXYZ using an Effective Coverage Map
2012 (English)Conference paper, Presentation (Other academic)
The goal of the present work is to reduce the number of the training samples used in our color prediction model based on CIEXYZ using an Effective Coverage Map while keeping satisfying prediction. A general approach is proposed in this paper to choose the best reference combination for the training samples. The approach is based on the dot gain behavior of each primary ink, which is characterized by three curves using CIEXYZ tri-stimulus values. The proposed approach is built in our model to predict the color values for the color prints using two different devices, i.e. a laser printer and an inkjet printer. For the laser printer the number of the training samples is reduced from 125 to 64 while still giving quite good result. The approach also shows that for the test laser printer it is possible to further cut this number to 53 with a satisfying result. For the inkjet printer the number of training samples for our model is reduced from 125 to 79 or 64, both giving satisfying results.
Place, publisher, year, edition, pages
Color Prediction, Dot Gain, Color Difference, effective coverage map
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-76849OAI: oai:DiVA.org:liu-76849DiVA: diva2:517005
6th European Conference on Color in Graphics, Imaging,and Vision, May 6-9, Amsterdam, The Netherland (CGIV 2012)