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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010351</journal-id>
      <journal-title>Conference on Colour in Graphics, Imaging, and Vision</journal-title>
      <abbrev-journal-title>conf colour graph imag vis</abbrev-journal-title>
      <issn pub-type="ppub">2158-6330</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/CGIV.2010.5.1.art00066</article-id>
      <article-id pub-id-type="sici">2158-6330(20100101)2010:1L.423;1-</article-id>
      <article-id pub-id-type="publisher-id">cgiv_v2010n1/splitsection66.xml</article-id>
      <article-id pub-id-type="other">/ist/cgiv/2010/00002010/00000001/art00066</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Evaluation of Performance of Twelve Color-Difference Formulae Using Two NCSU Experimental Datasets</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Shamey</surname>
            <given-names>Renzo</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Hinks</surname>
            <given-names>David</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Melgosa</surname>
            <given-names>Manuel</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Luo</surname>
            <given-names>Ronnier</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Cui</surname>
            <given-names>Guihua</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Huertas</surname>
            <given-names>Rafael</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>C&#xE1;rdenas</surname>
            <given-names>Lina</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Lee</surname>
            <given-names>Seung Geol</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>01</day>
        <month>01</month>
        <year>2010</year>
      </pub-date>
      <volume>2010</volume>
      <issue>1</issue>
      <fpage>423</fpage>
      <lpage>428</lpage>
      <permissions>
        <copyright-year>2010</copyright-year>
      </permissions>
      <abstract>
        <p>We previously reported the performance of four color difference equations around the CIE 1978 blue color center (NCSU-B1) using various statistical measures [1,2]. In this study we employed the standardized residual sum of squares (STRESS) [3] index to test the performance of twelve
 colordifference formulae using two experimental NCSU datasets. The first dataset (NCSU-B1) included 66 sample pairs around the CIE 1978 blue color center and the second dataset (NCSU-2) contained 69 sample pairs around 13 color centers [4]. In the first dataset 26 observers made a total of
 5148 assessments of sample pairs with small color differences (&#x394;E*<sub>ab</sub>&lt;5) while the second dataset involved 20,700 assessments by 100 observers from four different geographical regions of the world (25 in each region). Each pair in both sets was assessed by each color normal
 observer in three separate sittings on separate days and the average of assessments was calculated. For the samples in the first dataset a custom AATCC standard gray scale was employed to assess the magnitude of difference between colored samples. A third-degree polynomial equation was used
 to convert gray scale ratings to visual differences (&#x394;V). In the second study a novel perceptually linear gray scale was developed and a linear function was used to obtain visual differences. Based on the analysis of STRESS index results the DIN99d equation gave the best results for both
 datasets, and the CIELAB equation the worst.</p>
      </abstract>
    </article-meta>
  </front>
</article>
