RSurf - the Efficient Texture-Based Descriptor for Fluorescence Microscopy Images of HEp-2 Cells
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00073550" target="_blank" >RIV/00216224:14330/14:00073550 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICPR.2014.215" target="_blank" >http://dx.doi.org/10.1109/ICPR.2014.215</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICPR.2014.215" target="_blank" >10.1109/ICPR.2014.215</a>
Alternative languages
Result language
angličtina
Original language name
RSurf - the Efficient Texture-Based Descriptor for Fluorescence Microscopy Images of HEp-2 Cells
Original language description
In biomedical image analysis, object description and classification tasks are very common. Our work relates to the problem of classification of Human Epithelial (HEp-2) cells. Since the crucial part of each classification process is the feature extraction and selection, much attention should be concentrated to the development of proper image descriptors. In this article, we introduce a new efficient texture-based image descriptor for HEp-2 images. We compare proposed descriptor with LBP, Haralick features (GLCM statistics) and Tamura features using the public MIVIA HEp-2 Images Dataset. Our descriptor outperforms all previously mentioned approaches and the classifier based solely on the proposed descriptor is able to achieve the accuracy as high as 87.8%.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GBP302%2F12%2FG157" target="_blank" >GBP302/12/G157: Dynamics and Organization of Chromosomes in the Cell Cycle and during Differentiation under Normal and Pathological Conditions</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
22nd International Conference on Pattern Recognition
ISBN
9781479952083
ISSN
1051-4651
e-ISSN
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Number of pages
6
Pages from-to
1194-1199
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos, California
Event location
Stockholm, Sweden
Event date
Jan 1, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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