Selected article for: "local level and spatial information"
Author: Saban Ozturk; Umut Ozkaya; Mucahid Barstugan
Title: Classification of Coronavirus Images using Shrunken Features
  • Document date: 2020_4_6
    • ID: 2l1zw19o_23
    Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.03.20048868 doi: medRxiv preprint Local Binary Grey Level Co-occurrence Matrix; the LBGLCM feature extraction method is a hybrid technique used together with Local Binary Pattern (LBP) and GLCM. LBP technique is applied to the grey-level image. Then, GLCM features are extracted from the obtained LBP texture image. GLCM method takes into a.....
    Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.03.20048868 doi: medRxiv preprint Local Binary Grey Level Co-occurrence Matrix; the LBGLCM feature extraction method is a hybrid technique used together with Local Binary Pattern (LBP) and GLCM. LBP technique is applied to the grey-level image. Then, GLCM features are extracted from the obtained LBP texture image. GLCM method takes into account neighboring pixels at the feature extraction stage. It does not perform any operation on other local patterns in the image. Textural and spatial information in the image is obtained together with the LBGLCM method. Simultaneous acquisition of this information increases the availability of the LBGLCM algorithm in image processing applications [22] .

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