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Automatic color patch selection for painting identification

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A new method to define a digital signature of a painting is presented. This signature is composed by a set of patches that are automatically selected as the images regions containing the most relevant information.

The region selection is applied on a combination of saliency maps related to different features concerning intensity, color and visual saliency. We present the generation of the feature saliency map exploiting low-level feature representations, and the new algorithm for selecting the most relevant regions. The position and actual size of these regions is not a-priori fixed but is function of the saliency maps, i.e. of the painting content.

We present the experimental results on several painting, discussing the trade-offs among image features parameters values and the selected regions.
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Document Type: Research Article

Publication date: January 1, 2008

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    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 papers for details.

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