Journal article Open Access
Bably Dolly; Deepa Raj
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="041" ind1=" " ind2=" "> <subfield code="a">eng</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">segmentation, image retrieval, color feature</subfield> </datafield> <controlfield tag="005">20211027134850.0</controlfield> <controlfield tag="001">5602263</controlfield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">Assistant professor , Department of Computer Science Babasaheb Bhim Rao Ambedkar University</subfield> <subfield code="a">Deepa Raj</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">Publisher</subfield> <subfield code="4">spn</subfield> <subfield code="a">Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">746782</subfield> <subfield code="z">md5:a5eb6582300f95062bc0c9d44f366af3</subfield> <subfield code="u">https://zenodo.org/record/5602263/files/B3163129219.pdf</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2019-12-30</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">openaire</subfield> <subfield code="o">oai:zenodo.org:5602263</subfield> </datafield> <datafield tag="909" ind1="C" ind2="4"> <subfield code="c">454-460</subfield> <subfield code="n">2</subfield> <subfield code="p">International Journal of Engineering and Advanced Technology (IJEAT)</subfield> <subfield code="v">9</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="u">Ph.D., Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow.</subfield> <subfield code="a">Bably Dolly</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Color Based Image Retrieval by Combining Various Features</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield> <subfield code="a">Creative Commons Attribution 4.0 International</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="650" ind1="1" ind2=" "> <subfield code="a">ISSN</subfield> <subfield code="0">(issn)2249-8958</subfield> </datafield> <datafield tag="650" ind1="1" ind2=" "> <subfield code="a">Retrieval Number</subfield> <subfield code="0">(handle)B3163129219/2019©BEIESP</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><p>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.</p></subfield> </datafield> <datafield tag="773" ind1=" " ind2=" "> <subfield code="n">issn</subfield> <subfield code="i">isCitedBy</subfield> <subfield code="a">2249-8958</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.35940/ijeat.B3163.129219</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">article</subfield> </datafield> </record>
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