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                <article article-type="research-article">
                <front>
                    <journal-meta>
                    <journal-id journal-id-type="publisher-id">cic</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">2166-9635</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/CIC.2022.30.1.44</article-id>
                    <article-id pub-id-type="publisher-id">44</article-id>
                    <article-categories>
                        <subj-group>
                        <subject>Regular Article</subject>
                        </subj-group>
                    </article-categories>
                    <title-group>
                        <article-title>Predicting Pigment Color Degradation with Time Series Models</article-title>
                    </title-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                            <surname>Ciortan</surname>
                            <given-names>Irina-Mihaela </given-names>
                           </name> <xref ref-type="aff" rid="aff1author1"/></contrib><aff id="aff1author1">Norwegian University of Science and Technology, Norway</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                            <surname>Poulsson</surname>
                            <given-names>Tina Grette</given-names>
                           </name> <xref ref-type="aff" rid="aff2author2"/></contrib><aff id="aff2author2">National Museum of Norway, Norway</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                            <surname>George</surname>
                            <given-names>Sony </given-names>
                           </name> <xref ref-type="aff" rid="aff1author3"/></contrib><aff id="aff1author3">Norwegian University of Science and Technology, Norway</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                            <surname>Hardeberg</surname>
                            <given-names>Jon Yngve</given-names>
                           </name> <xref ref-type="aff" rid="aff1author4"/></contrib><aff id="aff1author4">Norwegian University of Science and Technology, Norway</aff></contrib-group><abstract>
                    <title>Abstract</title>
                    <p>The colors of pigments and dyes are affected by light exposure. Light-induced color change has an impact on various industrial and artistic applications where colored materials are frequently exposed to light throughout their life-cycle. For this reason, it is beneficial to understand the fading behaviour of pigments and simulate future degradation. In this article, we are proposing a method to forecast color change of pigments based on time series analysis. To begin with, we collect fading data from real objects with a microfadeometer, which records the color coordinates after every second of light exposure. Then, we treat this data as a time series, test for its stationarity and fit it with autoregressive integrated moving average (ARIMA) models. Finally, using a train-test split, we validate the accuracy of the ARIMA models in predicting color degradation of pigments and dyes.</p>
                    </abstract><pub-date>
                        <day>15</day>
                        <month>11</month>
                        <year>2022</year>
                        </pub-date><volume>30</volume>
                    <issue-acronym></issue-acronym>
                    <issue-title>30th Color and Imaging Conference</issue-title>
                    <issue>1</issue>
                    <fpage>250</fpage>
                    <lpage>257</lpage>
                    <permissions>
                         <copyright-statement>©2022 Society for Imaging Science and Technology</copyright-statement>
                        <copyright-year>2022</copyright-year>
                    </permissions><kwd-group><kwd>microfading</kwd><kwd>pigment lightfastness</kwd><kwd>time series</kwd><kwd>ARIMA</kwd></kwd-group></article-meta>
                </front>
                </article>