1 Ocak 2023 Dergi makalesi Açık Erişim

Azimjonov, Jahongir; Ozmen, Ahmet; Varan, Metin

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/267044</identifier>
  <creators>
    <creator>
      <creatorName>Azimjonov, Jahongir</creatorName>
      <givenName>Jahongir</givenName>
      <familyName>Azimjonov</familyName>
      <affiliation>Andijan State Univ, Chungbuk Natl Univ, Sch Informat &amp; Commun Engn, Cheongju 28644, South Korea</affiliation>
    </creator>
    <creator>
      <creatorName>Ozmen, Ahmet</creatorName>
      <givenName>Ahmet</givenName>
      <familyName>Ozmen</familyName>
      <affiliation>Sakarya Univ, Dept Software Engn, TR-54054 Serdivan, Sakarya, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Varan, Metin</creatorName>
      <givenName>Metin</givenName>
      <familyName>Varan</familyName>
      <affiliation>Sakarya Univ Appl Sci, Dept Elect &amp; Elect Engn, TR-54187 Serdivan, Sakarya, Turkiye</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A Vision-Based Real-Time Traffic Flow Monitoring System For Road Intersections</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2023</publicationYear>
  <dates>
    <date dateType="Issued">2023-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/267044</alternateIdentifier>
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  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1007/s11042-023-14418-w</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;In this study, a vision based real-time traffic flow monitoring system has been developed to extract statistics passes through the intersections. A novel object tracking and data association algorithms have been developed using the bounding-box properties to estimate the vehicle trajectories. Then, rich traffic flow information such as directional and total counting, instantaneous and average speed of vehicles are calculated from the predicted trajectories. During the study, various parameters that affect the accuracy of vision based systems are examined such as camera locations and angles that may cause occlusion or illusion problems. In the last part, sample video streams are processed using both Kalman filter and new centroid-based algorithm for comparative study. The results show that the new algorithm performs 9.18% better than Kalman filter approach in general.&lt;/p&gt;</description>
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