An Automated Color Image Arrangement Method Based on Histogram Matching

We propose a novel color image arrangement method using an elastic transform based on histogram matching on some kinds of axes. The axes include Lightness axis and PC axes obtained from Principal Component Analysis (PCA) in the RGB three-dimensional vector space that is an attribute space of color i...

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Bibliographic Details
Published in2013 International Conference on Biometrics and Kansei Engineering pp. 31 - 34
Main Authors Kawakami, Yusuke, Hattori, Tetsuo, Kutsuna, Daisuke, Matsushita, Haruna, Imai, Yoshiro, Kawano, Hiromichi, Rajapakse, R. P. C. Janaka
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2013
Subjects
Automated color arrangement
Color
Curvature
Density functional theory
elastic transform
Gaussian distribution
histogram matching
Histograms
HMGD
Image color analysis
Principal component analysis
Single-peakedness
Transforms
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Summary:We propose a novel color image arrangement method using an elastic transform based on histogram matching on some kinds of axes. The axes include Lightness axis and PC axes obtained from Principal Component Analysis (PCA) in the RGB three-dimensional vector space that is an attribute space of color image. In this paper, we mainly present the principle of its automated color arrangement method especially based on HMGD (Histogram Matching based on Gaussian Distribution). And we describe that the automated method applies the HMGD to input color image only if the image has single-peaked ness in its histogram on the focused axis. In order to detect the single-peaked ness of histogram, the method uses a curvature computation for the cumulative histogram. We show that the method brings about a good sensibility effect (or Kansei effect) in the case of applying the HMGD onto Lightness axis.
DOI:10.1109/ICBAKE.2013.7