Journal article Open Access

Color Based Image Retrieval by Combining Various Features

Bably Dolly; Deepa Raj


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/5602263</identifier>
  <creators>
    <creator>
      <creatorName>Bably Dolly</creatorName>
      <affiliation>Ph.D., Department of Computer Science, Babasaheb  Bhimrao Ambedkar University, Lucknow.</affiliation>
    </creator>
    <creator>
      <creatorName>Deepa Raj</creatorName>
      <affiliation>Assistant professor , Department of Computer Science  Babasaheb Bhim Rao Ambedkar University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Color Based Image Retrieval by Combining Various  Features</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>segmentation, image retrieval, color feature</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">B3163129219/2019©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/5602263</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.B3163.129219</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;Content based image retrieval system retrieve the images according to the strong feature related to desire as color, texture and shape of an image. Although visual features cannot be completely determined by semantic features, but still semantic features can be integrate easily into mathematical formulas. This paper is focused on retrieval of images within a large image collection, based on color projection by applying segmentation and quantification on different color models and compared for good result. This method is applied on different categories of image set and evaluated its retrieval rate in different models.&lt;/p&gt;</description>
  </descriptions>
</resource>
18
17
views
downloads
Views 18
Downloads 17
Data volume 12.7 MB
Unique views 18
Unique downloads 17

Share

Cite as