This article presents a new methodology for the color accuracy optimization of a two-dimensional digital reproduction. Selecting a training set referring to the colorimetric content of the object to be reproduced results in a significant improvement of the color accuracy of an RGB reproduction. Some authors have developed methodologies for color accuracy optimization that involve the creation of specific custom-made reference targets. The methodology presented here does not involve the creation of custom-made targets, as the reference colors are selected directly on the object. In fact, a clusterization is performed on the RGB image of the object and a set of representative colors is achieved. For each RGB representative color, the corresponding CIELAB value is measured and a training set is obtained that can be used to define a transformation that maps all RGB values into CIELAB values. The experiments conducted show that using this methodology considerably improves color accuracy. (C) 2011 Society for Imaging Science and Technology. [DOI: 10.2352/J.ImagingSci.Technol.2011.55.6.060503]

Object-Specific and Target-Free Procedure for the Color Accuracy of a Two-Dimensional Digital Reproduction

Selva M;Stefani L;
2011

Abstract

This article presents a new methodology for the color accuracy optimization of a two-dimensional digital reproduction. Selecting a training set referring to the colorimetric content of the object to be reproduced results in a significant improvement of the color accuracy of an RGB reproduction. Some authors have developed methodologies for color accuracy optimization that involve the creation of specific custom-made reference targets. The methodology presented here does not involve the creation of custom-made targets, as the reference colors are selected directly on the object. In fact, a clusterization is performed on the RGB image of the object and a set of representative colors is achieved. For each RGB representative color, the corresponding CIELAB value is measured and a training set is obtained that can be used to define a transformation that maps all RGB values into CIELAB values. The experiments conducted show that using this methodology considerably improves color accuracy. (C) 2011 Society for Imaging Science and Technology. [DOI: 10.2352/J.ImagingSci.Technol.2011.55.6.060503]
2011
Istituto di Fisica Applicata - IFAC
CIELAB space
color accuracy
clusterization
k-means clustering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/279759
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