DocumentCode :
2770153
Title :
Color reproduction by means of a Compactly Supported Radial Basis Function space mapping
Author :
Rodriguez, Ladys ; Diago, Luis ; Hagiwara, Ichiro ; Magoules, Frederic
Author_Institution :
Dept. of Mech. Eng., Tokyo Inst. of Technol., Tokyo, Japan
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1
Lastpage :
5
Abstract :
Colors play an important role for customers to find their preference. The perception of the color depends on the devices used to show the colors and it changes with the color transformation between one device and another. This paper proposes an iterative approach for color reproduction of industrial manufacturer samples in a commercial printer device using a Compactly-Supported Radial Basis Functions (CSRBF) space mapping which avoids unnecessary printings during color reproduction. In order to illustrate an application of the proposed color reproduction, four users manually adjusted 28 samples of colors provided by painting manufacturers. The 28 samples are automatically reproduced with good accuracy according to the International Commission on Illumination (CIE) color difference formula using the proposed CSRBF-based iterative reproduction approach. The proposed CSRBF-based approach is compared with a related Artificial Neural Network (ANN) mapping. Proposed CSRBF mapping reproduced the 100% of the colors within a threshold for industrial process taking only 3.1 sec, while the ANN mapping only reproduced the 78.57% of the colors in much time (60.1 sec).
Keywords :
psychology; radial basis function networks; visual perception; ANN mapping; CIE; CSRBF-based iterative reproduction approach; International Commission on Illumination; artificial neural network mapping; color difference formula; color reproduction; color transformation; commercial printer device; compactly supported radial basis function space mapping; industrial manufacturer samples; industrial process; iterative approach; Artificial neural networks; Color; Image color analysis; Interpolation; Iterative methods; Paints; Printers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
ISSN :
2161-4393
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
Type :
conf
DOI :
10.1109/IJCNN.2012.6252420
Filename :
6252420
Link To Document :
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