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@misc{1317735, author = {Majtner, Tomáš and Svoboda, David}, keywords = {image descriptor; Pattern recognition; Gabor features; MPEG-7 Edge Histogram Descriptor;}, language = {eng}, institution = {Masarykova univerzita}, organization = {Masarykova univerzita}, title = {2D/3D Gabor Features and 2D/3D MPEG-7 EHD Features}, url = {http://cbia.fi.muni.cz/projects/2d/3d-gabor--2d/3d-mpeg-7-ehd-features.html}, year = {2015} }
TY - ID - 1317735 AU - Majtner, Tomáš - Svoboda, David PY - 2015 TI - 2D/3D Gabor Features and 2D/3D MPEG-7 EHD Features KW - image descriptor KW - Pattern recognition KW - Gabor features KW - MPEG-7 Edge Histogram Descriptor; UR - http://cbia.fi.muni.cz/projects/2d/3d-gabor--2d/3d-mpeg-7-ehd-features.html L2 - http://cbia.fi.muni.cz/projects/2d/3d-gabor--2d/3d-mpeg-7-ehd-features.html N2 - The recognition of patterns with focus on texture and shape analysis is still very hot topic, especially in biomedical image processing. In this article, we introduce 3D extensions of well-known approaches for this particular area. We focus on the collection of MPEG-7 image descriptors, specifically on the Edge Histogram Descriptor (EHD) and Gabor features, which are the core of the Homogeneous Texture Descriptor (HTD). The proposed extensions are evaluated on the dataset consisting of three classes of 3D volumetric biomedical images. Two different classifiers, namely k-NN and Multi-Class SVM, are used to evaluate the proposed algorithms. According to the presented tests, the proposed 3D extensions clearly outperform their 2D equivalents in the classification tasks. ER -
MAJTNER, Tomáš a David SVOBODA. \textit{2D/3D Gabor Features and 2D/3D MPEG-7 EHD Features}. 2015.
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