Affiliation:
1. 1Doctoral Student, Spectral Color Research Lab, School of Computing, University of Eastern Finland
2. 2Computer Science and Engineering Discipline, Khulna University, Khulna
Abstract
AbstractThis article presents a comprehensive study of 30
color transforms to accurately segment images of halftone
prints and thus calculating the parameters of a color prediction
model. The transforms are evaluated combining
three metrics: the model accuracy,Otsu’s discriminant, and
correlation coefficients of histograms. Hierarchical cluster
analysis is applied to determine the thresholds to segment
the image histogram into paper, ink and mixed area.
Among the 30 different transforms discussed in this article,
21 channels are of 7 color space models (RGB, CMYK,
CIELAB, HSV, YIQ, YCbCr, and XYZ) and the other 9 channels
are specially designed. Notable increase in model accuracy
validates the segmentation accuracy and the necessity
of choosing the appropriate transform. A set of 180
halftone images of different print properties (such as paper,
halftone, ink and printing technology) has been used
for the evaluation. It is found that, the most appropriate
transform depends on the type of primary ink, but the corresponding
transforms in CMYK color space model have
shown consistent performance. CMYK-C, XYZ-Y and LAB-B
are the best transforms for Cyan, Magenta and Yellow ink
color respectively. YIQ-I and HSV-S are good candidates if a
single transform is to be chosen for all primary ink colors.
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