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<journal-id journal-id-type="publisher">global-journal-of-computer-science-and-technology</journal-id>
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<journal-title>Global Journal of Computer Science and Technology</journal-title>
</journal-title-group>
<issn publication-format="print">0975-4350</issn>
<issn publication-format="electronic">0975-4172</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
<self-uri xlink:href="https://globaljournals.org/journal-seo-export/jats/74062.xml" />
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<article-id pub-id-type="publisher-id">74062</article-id>
<title-group>
<article-title>Efficient Image Retrieval Based on Texture Features Using Concept of Histogram</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Sadinen</surname><given-names>Neelima</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
</contrib-group>
<aff id="aff1">INDIA</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2012-05-15">
<day>15</day>
<month>05</month>
<year>2012</year>
</pub-date>
<volume>12</volume>
<issue>5</issue>
<fpage>29</fpage>
<lpage>35</lpage>
<abstract><p>Image retrieval is fast growing research oriented area now days. As information retrieval plays a major role in transmitting knowledge both in the forms of text and images, image retrieval got a major focus. In this paper we integrated the Histogram Intersection measure method to compare the query image with database images; by this approach we can measure over-all similarity between images, by incorporating all local properties of the texture histograms of the images through which we proved that our approach in retrieving the image is accurate.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>Histogram</kwd>
<kwd>image</kwd>
<kwd>texture</kwd>
<kwd>database</kwd>
<kwd>retrieval</kwd>
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<self-uri content-type="pdf" xlink:href="https://globaljournals.org/GJCST_Volume12/5-Efficient-Image-Retrieval-Based.pdf" />
<self-uri content-type="html" xlink:href="https://globaljournals.org/scholarly-articles/efficient-image-retrieval-based-on-texture-features-using-concept-of-histogram/" />
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<title>Full Text</title>
<p>Image retrieval is fast growing research oriented area now days. As information retrieval plays a major role in transmitting knowledge both in the forms of text and images, image retrieval got a major focus. In this paper we integrated the Histogram Intersection measure method to compare the query image with database images; by this approach we can measure over-all similarity between images, by incorporating all local properties of the texture histograms of the images through which we proved that our approach in retrieving the image is accurate.</p>
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