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                    <article article-type="research-article">
                    <front>
                        <journal-meta>
                        <journal-id journal-id-type="publisher-id">ei</journal-id>
                        <journal-title>Electronic Imaging</journal-title>
                        <issn pub-type="ppub">2470-1173</issn><issn pub-type="epub">2470-1173</issn>
                        <publisher>
                            <publisher-name>Society for Imaging Science and Technology</publisher-name>
                            <publisher-loc>IS&amp;T 7003 Kilworth Lane, Springfield, VA 22151 USA</publisher-loc>
                        </publisher>
                        </journal-meta>
                        <article-meta>
                        <article-id pub-id-type="doi">10.2352/EI.2022.34.10.IPAS-345</article-id>
                        <article-id pub-id-type="publisher-id">IPAS-345</article-id>
                        <article-categories>
                            <subj-group>
                            <subject>Article</subject>
                            </subj-group>
                        </article-categories>
                        <title-group>
                            <article-title>Rapid circle detection through fusion of summative statistics of edge components</article-title>
                        </title-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Craver</surname>
                                <given-names>Scott A.</given-names>
                               </name> <xref ref-type="aff" rid="aff1author1"/></contrib> <aff id="aff1author1">Binghamton University, United States</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Angoy</surname>
                                <given-names>Pheona </given-names>
                               </name> <xref ref-type="aff" rid="aff1author2"/></contrib> <aff id="aff1author2">Binghamton University, United States</aff></contrib-group><abstract>
                        <title>Abstract</title>
                        <p>Circle detection of edge images can involve significant time and memory requirements, particularly if the circles have unknown radii over a large range. We describe an algorithm that processes an edge image in a single linear pass, compiling statistics of connected components that can be used by two distinct least square methods. Because the compiled statistics are all sums, these components can then be quickly merged without any further examination of image pixels. Fusing multiple circle detectors allows more powerful circle detection. The resulting algorithm is of linear complexity in the number of image pixels, and quadratic complexity in a much smaller number of cluster statistics.</p>
                        </abstract><pub-date>
                            <day>16</day>
                            <month>01</month>
                            <year>2022</year>
                            </pub-date><volume>34</volume>
                        <issue-acronym>IPAS</issue-acronym>
                        <issue>10</issue>
                        <fpage>345-1</fpage>
                        <lpage>345-5</lpage>
                        <permissions>
                             <copyright-statement>© 2022, Society for Imaging Science and Technology</copyright-statement>
                            <copyright-year>2022</copyright-year>
                        </permissions><kwd-group><kwd>image processing</kwd><kwd> circle detection</kwd><kwd> least squares fit</kwd></kwd-group></article-meta>
                    </front>
                    </article>