Feature Selection on Affine Moment Invariants in Relation to Known Dependencies

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Feature Selection on Affine Moment Invariants in Relation to Known Dependencies

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Feature Selection on Affine Moment Invariants in Relation to Known Dependencies

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GA15-16928S" target="_blank" >GA15-16928S: Invarianty a adaptivní reprezentace digitálních obrazů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Computer Analysis of Images and Patterns : 17th International Conference, CAIP 2017

ISBN

978-3-319-64698-5

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

285-295

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Ystad

Datum konání akce

22. 8. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000432084600024