• DocumentCode
    152173
  • Title

    A novel texture classification method based on Hessian matrix and principal curvatures

  • Author

    Alpaslan, Nuh ; Hanbay, Kazim ; Hanbay, Davut ; Talu, M. Fatih

  • Author_Institution
    Bilgisayar Muhendisligi Bolumu, Inonu Univ., Malatya, Turkey
  • fYear
    2014
  • fDate
    23-25 April 2014
  • Firstpage
    160
  • Lastpage
    163
  • Abstract
    In 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.
  • Keywords
    feature extraction; image classification; image texture; CoHOG feature extraction methods; HOG feature extraction methods; Hessian matrix; classification performance; principal curvature information; texture classification method; texture feature extraction; texture images; Art; Computer vision; Conferences; Feature extraction; Field programmable gate arrays; Histograms; Signal processing; CoHOG; HOG; Hessian matris; Temel Eğrilikler;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2014 22nd
  • Conference_Location
    Trabzon
  • Type

    conf

  • DOI
    10.1109/SIU.2014.6830190
  • Filename
    6830190