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dc.contributor.authorAlpaslan, N. and Hanbay, K. and Hanbay, D. and Talu, M.F.
dc.date.accessioned2021-04-08T12:09:38Z
dc.date.available2021-04-08T12:09:38Z
dc.date.issued2014
dc.identifier10.1109/SIU.2014.6830190
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84903758464&doi=10.1109%2fSIU.2014.6830190&partnerID=40&md5=ec9b847e762c652bd9723693a44711b3
dc.identifier.urihttp://acikerisim.bingol.edu.tr/handle/20.500.12898/4865
dc.description.abstractIn this study, in order to obtain similar effect with conventional gradient operation and extract more robust feature for texture, we use the principal curvature informations instead of the gradient calculation. Through this methods, sharp and important informations about the texture images were obtained by analyzing images of the second order. Considering the classification results obtained, it is shown that the proposed method improve the performance of original CoHOG and HOG feature extraction methods. As a result of experiments on datasets with different characteristics, it is seen that, the proposed method has higher classification performance. © 2014 IEEE.
dc.language.isoTurkish
dc.source2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
dc.titleA novel texture classification method based on Hessian matrix and principal curvatures [Hessian matrisi ve temel eǧriliklere dayanan yeni bir doku siniflandirma metodu]


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