Feature Selection on Affine Moment Invariants in Relation to Known Dependencies

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00476980" target="_blank" >RIV/67985556:_____/17:00476980 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-64698-5_24" target="_blank" >http://dx.doi.org/10.1007/978-3-319-64698-5_24</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-64698-5_24" target="_blank" >10.1007/978-3-319-64698-5_24</a>

Result language
angličtina
Original language name
Feature Selection on Affine Moment Invariants in Relation to Known Dependencies
Original language description
Moment invariants are one of the techniques of feature extraction frequently used for pattern recognition algorithms. A moment is a projection of function into polynomial basis and an invariant is a function returning the same value for an input with and without particular class of degradation. Several techniques of moment invariant creation exist often generating over-complete set of invariants. Dependencies in these sets are commonly in a form of complicated polynomials, further-nmore they can contain dependencies of higher orders. These theoretical dependencies are valid in the continuous domain but it is well known that in discrete cases are often invalidated by discretization. Therefore, it would be feasible to begin classi cation with such an over-completenset and adaptively nd the pseudo-independent set of invariants by the means of feature selection techniques. This study focuses on testing of the infuence of theoretical invariant dependencies in discrete pattern recognition applications.
Czech name
—
Czech description
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Project
<a href="/en/project/GA15-16928S" target="_blank" >GA15-16928S: Invariants and adaptive representations of digital images</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Computer Analysis of Images and Patterns : 17th International Conference, CAIP 2017
ISBN
978-3-319-64698-5
ISSN
—
e-ISSN
—
Number of pages
11
Pages from-to
285-295
Publisher name
Springer
Place of publication
Cham
Event location
Ystad
Event date
Aug 22, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000432084600024

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