Detailed Information on Publication Record
2014
Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy
MAJTNER, Tomáš and David SVOBODABasic information
Original name
Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy
Authors
MAJTNER, Tomáš (703 Slovakia, belonging to the institution) and David SVOBODA (203 Czech Republic, guarantor, belonging to the institution)
Edition
Los Alamitos, California, 4th International Conference on 3D Imaging (IC3D), p. 1-7, 7 pp. 2014
Publisher
IEEE Computer Society
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
20200 2.2 Electrical engineering, Electronic engineering, Information engineering
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
RIV identification code
RIV/00216224:14330/14:00074031
Organization unit
Faculty of Informatics
ISBN
978-1-4799-8023-9
UT WoS
000380557000005
Keywords in English
3D images; Edge Histogram Descriptor; Gabor filters; fluorescence microscopy
Tags
Tags
International impact, Reviewed
Změněno: 6/3/2015 15:45, RNDr. Ing. Bc. Tomáš Majtner, Ph.D.
Abstract
V originále
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.
Links
GA14-22461S, research and development project |
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MUNI/A/0855/2013, interní kód MU |
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