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dc.contributor.authorVipparthi, S.K.-
dc.contributor.authorMurala, S.-
dc.contributor.authorNagar, S.K.-
dc.contributor.authorGonde, A.B.-
dc.date.accessioned2016-08-23T06:55:50Z-
dc.date.available2016-08-23T06:55:50Z-
dc.date.issued2016-08-23-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/268-
dc.description.abstractIn this chapter, a new feature descriptor, local mesh correlation histograms (LMeCH) is proposed for content-based image retrieval (CBIR). The LMeCH integrates the local mesh patterns (LMeP) and grayscale joint histogram. Firstly, the LMeP features are extracted from the image and then the joint histogram is constructed between the LMeP and grayscale value of center pixel. The process of joint histogram is able to extract the efficient image features from the databases. The retrieval performance of the proposed method is tested on two bench mark OASIS-MRI and NEMA-CT biomedical image databases. The experimental results show a significant improvement in terms of precision, recall, average retrieval precision (ARP) and average retrieval rate (ARR) when compared with other standard image retrieval approaches on the same database.en_US
dc.language.isoen_USen_US
dc.titleAn Expert Local Mesh Correlation Histograms for Biomedical Image Indexing and Retrievalen_US
dc.typeArticleen_US
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