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Extraction of Artists' Color Features of Art Paintings and its Application to Color Image Correction

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This paper proposes a method to extract artists' color features of art paintings, and correct the color-mismatch images of paintings based on artists' color features. First, we describe a standard image database consisting of famous oil paintings we captured directly, and an algorithm for extracting artists' color features based on the color distribution of the standard image data for each artist. The color distribution is analyzed by PCA and described with an ellipsoid to represent the standard color features for the artist. It is suggested that the color features for the respective artists are similar to the human visual assessment of their paintings. Next, the color correction is based on the coordinate transformation of pixel values in a color-mismatch image so that the color features of the mismatched image are fitted to the artist's color features in the standard image database. We present a correction algorithm using sRGB and CIELAB color spaces. Experiments are performed using samples of colormismatch images of the famous oil paintings.
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Document Type: Research Article

Publication date: January 1, 2013

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

    Please note: for Purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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