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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.2470-1173.2018.07.MWSF-158</article-id>
      <article-id pub-id-type="sici">2470-1173(20180128)2018:7L.1581;1-</article-id>
      <article-id pub-id-type="publisher-id">s6.phd</article-id>
      <article-id pub-id-type="other">/ist/ei/2018/00002018/00000007/art00006</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Blind Detection of Image Rotation and Angle Estimation</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Goljan</surname>
            <given-names>Miroslav</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>28</day>
        <month>01</month>
        <year>2018</year>
      </pub-date>
      <volume>2018</volume>
      <issue>7</issue>
      <fpage>158-1</fpage>
      <lpage>158-10</lpage>
      <permissions>
        <copyright-year>2018</copyright-year>
      </permissions>
      <abstract>
        <p>The reliability of many digital forensic techniques can be negatively affected by geometrical transforms applied to the image under investigation because it breaks pixel-topixel synchronization needed for example for forensic methods that rely on sensor fingerprints. The geometrical
 transform typically needs to be detected and then its parameters estimated to allow subsequent successful and reliable forensic analysis. This paper focuses on blind detection of rotation and estimation of the angle by which the image was rotated. The proposed method utilizes the so-called
 Linear Pattern (LP) as a global template. In particular, no side information, such as watermark or the EXIF header, is required. The method is generally applicable whenever the image under investigation had a sufficiently strong LP before rotation. The performance of the method is assessed
 experimentally and by comparing to previous art. The main advantage of the proposed method is its accuracy for estimating small rotation angles (less than 3 degrees). It will also work after resizing.</p>
      </abstract>
      <kwd-group>
        <kwd>image forensics</kwd>
        <kwd>image processing history</kwd>
        <kwd>image transform</kwd>
        <kwd>rotation estimation</kwd>
        <kwd>blind estimation</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
