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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"/>
      <publisher>
        <publisher-name>Society of Imaging Science and Technology</publisher-name>
        <publisher-loc>7003 Kilworth Lane, Springfield, VA 22151, USA</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta><article-id pub-id-type="doi">10.2352/CIC.2013.21.1.art00036</article-id>
      <article-id pub-id-type="sici">2166-9635(20130101)2013:1L.200;1-</article-id>
      <article-id pub-id-type="publisher-id">cic_v2013n1/splitsection36.xml</article-id>
      <article-id pub-id-type="other">/ist/cic/2013/00002013/00000001/art00036</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>A Colour Palette for Automatic Detection of Blue-White Veil</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Madooei</surname>
            <given-names>Ali</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Drew</surname>
            <given-names>Mark S.</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>01</day>
        <month>01</month>
        <year>2013</year>
      </pub-date>
      <volume>2013</volume>
      <issue>1</issue>
      <fpage>200</fpage>
      <lpage>205</lpage>
      <permissions>
        <copyright-year>2013</copyright-year>
      </permissions>
      <abstract>
        <p>Colour assessment of pigmented skin lesions are essential for the diagnosis of malignant melanoma. However, visual interpretation of colour is subjective and prone to error. Computer programs can provide support to clinicians to overcome this subjectivity. So far, methods for colour
 analysis of this nature have utilised statistical classification models. This paper puts forward an alternative framework: an effort to reproduce the experience of human observer. The proposed method introduces a perceptually intuitive and semantically meaningful approach for colour and colour-related
 feature detection. As a case study, the task of automatic detection and segmentation of blue-white veil feature in dermoscopy images is examined. Our proposed method, as shown in our experiments, outperforms the prior art for this task, while it attempts to mimic the human perception of skin
 lesion colours.</p>
      </abstract>
    </article-meta>
  </front>
</article>
