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Local peak valley co-occurrence patterns: a new feature descriptor for image retrieval

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dc.contributor.author Agarwal, G.
dc.contributor.author Mishra, S. P.
dc.contributor.author Maurya, S.
dc.contributor.author Chaudhary, S.
dc.contributor.author Murala, S.
dc.date.accessioned 2021-10-10T10:05:08Z
dc.date.available 2021-10-10T10:05:08Z
dc.date.issued 2021-10-10
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/2993
dc.description.abstract In this paper, we propose a novel feature extraction and retrieval technique for medical images. Our proposed technique (LPVCoP) extracts similarity between grayscale images by using the relationship between reference pixel and its surrounding neighbor pixels through peak/valley edges which are obtained by taking directional derivatives. LPVCoP uses the co-occurrence among the first-order directional derivatives of reference pixel and second neighborhood adjoining pixels. The working of the proposed technique has been checked by implementing it in MATLAB and verifying the result on Computer Tomography (CT) databases. The retrieval results of the proposed technique are compared with the existing technique of image retrieval in terms of average retrieval rate (ARR) and average retrieval precision (ARP). The retrieval results of the LPVCoP are better as compared to the existing techniquesfor image retrieval. en_US
dc.language.iso en_US en_US
dc.subject Histogram en_US
dc.subject Local ternary patterns en_US
dc.subject Local Ternary Co- Occurrence patterns en_US
dc.subject Local binary patterns en_US
dc.subject Feature extraction en_US
dc.title Local peak valley co-occurrence patterns: a new feature descriptor for image retrieval en_US
dc.type Article en_US


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