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• W4226297198 abstract "Local Binary Pattern (LBP) based framework only uses a scalar threshold to binarize all magnitude vectors in <i>P</i> different directions around each center pixel of a texture image. Hence, the original LBP-based framework, in fact, can not precisely extract different magnitude features in <i>P</i> different directions around each center pixel. Furthermore, the value of magnitude vectors can have dramatic changes from coarse areas to flat areas in the same texture image. Therefore, using a scalar threshold calculated from whole texture image can not precisely binarize all magnitude vectors in coarse areas and flat areas simultaneously. To overcome these two drawbacks, we propose a novel adaptively binarizing magnitude vector (ABMV) method. Firstly, we adaptively calculate the average vector threshold <inline-formula><tex-math notation=LaTeX>$boldsymbol{vec{t}_{P}}$</tex-math></inline-formula> with <i>P</i> different directional values of all magnitude vectors to replace the scalar threshold <i>t</i> to binarize the magnitude vectors. The proposed ABMV method can more precisely extract the different magnitude features in <i>P</i> different directions around each center pixel. Secondly, we divide the original texture image into smaller sub-images and adaptively extract their average vector threshold from each sub-image separately. Because the correlation of the pixels in the same sub-image is stronger than that in a whole texture image, the ABMV method can more precisely extract different magnitude features from either coarse areas or flat areas. Finally, we introduce the proposed ABMV method into LBP-based framework. Extensive experiments are conducted on five representative texture databases: Outex, UIUC, CUReT, XU_HR and ALOT database. After introducing the ABMV method into CLBP, CLBC, BRINT and CJLBP, the classification accuracy and the robustness to noise of these methods can be significantly improved." @default.
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• W4226297198 date "2022-01-01" @default.
• W4226297198 modified "2023-09-26" @default.
• W4226297198 title "A Novel Adaptively Binarizing Magnitude Vector Method in Local Binary Pattern Based Framework for Texture Classification" @default.
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• W4226297198 doi "https://doi.org/10.1109/lsp.2022.3158199" @default.
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