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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010350</journal-id>
      <journal-title>Color and Imaging Conference</journal-title>
      <abbrev-journal-title>color imaging conf</abbrev-journal-title>
      <issn pub-type="ppub">2166-9635</issn><issn pub-type="epub"></issn>
      <publisher>
        <publisher-name>Society for Imaging Science and Technology</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.2352/ISSN.2169-2629.2018.26.145</article-id>
      <article-id pub-id-type="sici">2166-9635(20181112)2018:1L.145;1-</article-id>
      <article-id pub-id-type="publisher-id">s25.phd</article-id>
      <article-id pub-id-type="other">/ist/cic/2018/00002018/00000001/art00025</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Converting the Images without Glossiness into the Images with Glossiness by using Deep Photo Style Transfer</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Fukumoto</surname>
            <given-names>Kensuke</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Yoshii</surname>
            <given-names>Junki</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Hirasawa</surname>
            <given-names>Yuto</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Yamazoe</surname>
            <given-names>Takashi</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Yamamoto</surname>
            <given-names>Shoji</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Tsumura</surname>
            <given-names>Norimichi</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>12</day>
        <month>11</month>
        <year>2018</year>
      </pub-date>
      <volume>2018</volume>
      <issue>1</issue>
      <fpage>145</fpage>
      <lpage>150</lpage>
      <permissions>
        <copyright-year>2018</copyright-year>
      </permissions>
      <abstract>
        <p>In this paper, we propose an image conversion method to transfer the images without glossiness into the images with glossiness by using deep photo style transfer technique. The deep style photo transfer can be expected to reproduce a desired image with metallic appearance based on the
 texture transfer technique. Our practical challenge was performed to create the gold metallic image by transferring a style image of the gold ingot. Two kinds of stile images where one gold ingot and assembled mass of gold ingots were tested to verify how degree of complexity in style image
 is appropriate for our propose using deep neural network. In order to avoid an excessive loss of color balance, we also applied the YC<sub>r</sub>C<sub>b</sub> separation technique and used only Y component to learn the only style of gloss appearance. Moreover, the luminance and saturation
 of the style image were changed to investigate the influence into the converted appearance, since the converted appearances are expected to have the dependence with the contents of the images. These transferred results by changing the luminance and saturation of style image were evaluated
 by subjective evaluation using semantic differential method. As the results, it is found that the style image with an appropriate amount of contrast change is suitable for appropriate gloss appearance, then showed that there is appropriate selection of contrast in style image depending the
 contents of original images.</p>
      </abstract>
    </article-meta>
  </front>
</article>
