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@inproceedings{1204559, author = {Majtner, Tomáš and Svoboda, David}, address = {Los Alamitos, California}, booktitle = {4th International Conference on 3D Imaging (IC3D)}, doi = {http://dx.doi.org/10.1109/IC3D.2014.7032576}, keywords = {3D images; Edge Histogram Descriptor; Gabor filters; fluorescence microscopy}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Los Alamitos, California}, isbn = {978-1-4799-8023-9}, pages = {1-7}, publisher = {IEEE Computer Society}, title = {Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy}, year = {2014} }
TY - JOUR ID - 1204559 AU - Majtner, Tomáš - Svoboda, David PY - 2014 TI - Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy PB - IEEE Computer Society CY - Los Alamitos, California SN - 9781479980239 KW - 3D images KW - Edge Histogram Descriptor KW - Gabor filters KW - fluorescence microscopy N2 - The pattern recognition with focus on texture and shape analysis is still very hot topic, especially in biomedical image processing. In this article, we introduce 3D extension of well-known approaches for this particular area. We focus on the collection of MPEG-7 image descriptors, specifically on Edge Histogram Descriptor (EHD) and Gabor features, which are core of 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, proposed 3D extensions clearly outperforms their 2D equivalents in the classification tasks. ER -
MAJTNER, Tomáš and David SVOBODA. Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy. Online. In \textit{4th International Conference on 3D Imaging (IC3D)}. Los Alamitos, California: IEEE Computer Society, 2014, p.~1-7. ISBN~978-1-4799-8023-9. Available from: https://dx.doi.org/10.1109/IC3D.2014.7032576.
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