Image Retrieval based on Macro Regions

Image Retrieval based on Macro Regions

V Vijaya Kumar

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BIBI.NASREEN

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A.OBULESU

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1 Anurag Group of Institutions, Hyderabad, India

GJCST Volume 16 Issue F3

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Various image retrieval methods are derived using local features, and among them the local binary pattern (LBP) approach is very famous. The basic disadvantage of these methods is they completely fail in representing features derived from large or macro structures or regions, which are very much essential to represent natural images. To address this multi block LBP are proposed in the literature. The other disadvantage of LBP and LTP based methods are they derive a coded image which ranges 0 to 255 and 0 to 3561 respectively. If one wants to integrate the structural texture features by deriving grey level co-occurrence matrix (GLCM), then GLCM ranges from 256 x 256 and 3562 x 3562 in case of LBP and LTP respectively.

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No external funding was declared for this work.

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The authors declare no conflict of interest.

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V Vijaya Kumar. 2016. \u201cImage Retrieval based on Macro Regions\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 16 (GJCST Volume 16 Issue F3): .

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GJCST Volume 16 Issue F3
Pg. 25- 36

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-F Classification: I.3.3, B.4.2, H.2.8

Submission ReceivedDecember 6, 2015
RevisedDecember 6, 2015
Peer Review Double Blind
Handling Editor
Accepted January 4, 2016
Published January 15, 2016

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v1.2

Issue date

December 17, 2016

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English

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Total Score: 103

Country: India

Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision

Authors: V Vijaya Kumar, BIBI.NASREEN, A.OBULESU (PhD/Dr. count: 0)

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