Affine Moment Invariants of Tensor Fields
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F23%3A00571260" target="_blank" >RIV/67985556:_____/23:00571260 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-31435-3_20" target="_blank" >http://dx.doi.org/10.1007/978-3-031-31435-3_20</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-31435-3_20" target="_blank" >10.1007/978-3-031-31435-3_20</a>
Alternative languages
Result language
angličtina
Original language name
Affine Moment Invariants of Tensor Fields
Original language description
Tensor fields (TF) are a special kind of multidimensional data, in which a tensor is given for each point in space. Often, it is a 3 × 3 array in each voxel. To detect the patterns of interest in the field, special matching methods must be developed. We propose a method for the description and matching of TF patterns under an unknown affine transformation of the field. Transformations of TFs act not only in the spatial coordinates but also on the field values, which makes the detection more challenging. To measure the similarity between the template and the field patch, we propose original invariants with respect to affine transformations designed from moments. Their performance is demonstrated by experiments on real data from diffusion tensor imaging.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20206 - Computer hardware and architecture
Result continuities
Project
<a href="/en/project/GA21-03921S" target="_blank" >GA21-03921S: Inverse problems in image processing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Image Analysis: 23rd Scandinavian Conference, SCIA 2023
ISBN
978-3-031-31437-7
ISSN
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e-ISSN
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Number of pages
15
Pages from-to
299-313
Publisher name
Springer
Place of publication
Cham
Event location
Levi
Event date
Apr 18, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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