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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010604</journal-id>
      <journal-title>Electronic Imaging</journal-title>
      <issn pub-type="ppub">2470-1173</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.2470-1173.2018.13.IPAS-386</article-id>
      <article-id pub-id-type="sici">2470-1173(20180128)2018:13L.3861;1-</article-id>
      <article-id pub-id-type="publisher-id">s20.phd</article-id>
      <article-id pub-id-type="other">/ist/ei/2018/00002018/00000013/art00020</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Disparity Estimation Using Fast Motion-Search Algorithm and Local Image Characteristics</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Chang</surname>
            <given-names>Yong-Jun</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Ho</surname>
            <given-names>Yo-Sung</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>28</day>
        <month>01</month>
        <year>2018</year>
      </pub-date>
      <volume>2018</volume>
      <issue>13</issue>
      <fpage>386-1</fpage>
      <lpage>386-6</lpage>
      <permissions>
        <copyright-year>2018</copyright-year>
      </permissions>
      <abstract>
        <p>A stereo matching method estimates the disparity value between two correspondences in both stereo images. The disparity value represents the depth information of objects obtained from stereo images which have two different viewpoints. In many papers, the stereo matching method is tested
 under limited disparity conditions. These conditions follow configurations of test images. However, the disparity range in real applications is not known for those conditions and configurations. In this case, we have to check all pixels in the scan line to find the correspondence. Therefore,
 it is a time consuming task. Thus, we propose a fast disparity estimation method using the limited search range. The proposed method limits the disparity search range with the fast motion-search algorithm and local image characteristics.</p>
      </abstract>
      <kwd-group>
        <kwd>STEREO MATCHING</kwd>
        <kwd>DISPARITY MAP</kwd>
        <kwd>FAST MOTION-SEARCH</kwd>
        <kwd>LOCAL IMAGE CHARACTERISTIC</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
