Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge
Histogram Descriptor in Fluorescence Microscopy

D 2014

Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy

MAJTNER, Tomáš a David SVOBODA

Základní údaje

Originální název

Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy

Autoři

MAJTNER, Tomáš (703 Slovensko, domácí) a David SVOBODA (203 Česká republika, garant, domácí)

Vydání

Los Alamitos, California, 4th International Conference on 3D Imaging (IC3D), od s. 1-7, 7 s. 2014

Nakladatel

IEEE Computer Society

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Kód RIV

RIV/00216224:14330/14:00074031

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4799-8023-9

DOI

http://dx.doi.org/10.1109/IC3D.2014.7032576

UT WoS

000380557000005

Klíčová slova anglicky

3D images; Edge Histogram Descriptor; Gabor filters; fluorescence microscopy

Štítky

cbia-web

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 6. 3. 2015 15:45, RNDr. Ing. Bc. Tomáš Majtner, Ph.D.

Anotace

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.

Návaznosti

GA14-22461S, projekt VaV

Název: Vývoj a studium metod pro kvantifikaci živých buněk (Akronym: Live Cell Quantification)

Investor: Grantová agentura ČR, Development and Study of Methods for Live Cell Quantification

MUNI/A/0855/2013, interní kód MU

Název: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace III. (Akronym: FI MAV III.)

Investor: Masarykova univerzita, Rozsáhlé výpočetní systémy: modely, aplikace a verifikace III., DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

Citovat

MAJTNER, Tomáš a David SVOBODA. Texture Analysis Using 3D Gabor Features and 3D MPEG-7 Edge Histogram Descriptor in Fluorescence Microscopy. Online. In 4th International Conference on 3D Imaging (IC3D). Los Alamitos, California: IEEE Computer Society, 2014, s. 1-7. ISBN 978-1-4799-8023-9. Dostupné z: https://dx.doi.org/10.1109/IC3D.2014.7032576.

@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 a 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, s.~1-7. ISBN~978-1-4799-8023-9. Dostupné z: https://dx.doi.org/10.1109/IC3D.2014.7032576.

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