December 30, 2019 Journal article Open Access

LokeshVenkata Sai Mamidi; Pisupati Chaitanya; VikasUpadhyaya

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  <identifier identifierType="URL">https://zenodo.org/record/5599392</identifier>
  <creators>
    <creator>
      <creatorName>LokeshVenkata Sai Mamidi</creatorName>
      <affiliation>(B Tech) UG Scholar, Batch (2016- 2020), NIIT University,</affiliation>
    </creator>
    <creator>
      <creatorName>Pisupati Chaitanya</creatorName>
      <affiliation>(B Tech) UG Scholar, Batch (2016- 2020), NIIT University,</affiliation>
    </creator>
    <creator>
      <creatorName>VikasUpadhyaya</creatorName>
      <affiliation>(B Tech) UG Scholar, Batch (2016- 2020), NIIT University,</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Application of Image Processing In E-Commerce</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Image processing, application of data analysis, Otsu segmentation, measurement of a body part, Regression.</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">B3036129219/2019©BEIESP</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  &amp; Sciences Publication (BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2019-12-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5599392</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.B3036.129219</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The advancement and perpetual development in technology have made it possible to automate many processes. The proposed Algorithm in this research provides the framework to self-operate the process of quantifying the shoulder size of humans by taking the images of the user so that it can be utilized to find the shirt size of the human. The framework involves three important phases which are segmentation, edge detection, predicting shirt size. Since colour has no prominent role in measurement of size,otsu&amp;rsquo;s binary thresholding for image segmentation is used in order to get binary image which separates foreground and background. Along with predictive analysis particularly regression is used as the groundwork to predict shirt size. The main application is in the apparel industry such as online shopping to automate the size detection for more expeditious results. And in the custom made apparel stitching, rather than approaching the sea mster to take tape measurements our framework can be implemented therefore increasing the time efficiency.&lt;/p&gt;</description>
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