On the Null-Space of the Shape-Color Moment Invariants

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00508017" target="_blank" >RIV/67985556:_____/19:00508017 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-29888-3_32" target="_blank" >http://dx.doi.org/10.1007/978-3-030-29888-3_32</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-29888-3_32" target="_blank" >10.1007/978-3-030-29888-3_32</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On the Null-Space of the Shape-Color Moment Invariants

Popis výsledku v původním jazyce

In this paper, we extend the theory of the combined Shape-Color Affine Moment Invariants (SCAMIs) for recognition of color images, proposed originally by Gong et al. in [3]. Since in the real pictures the shape deformation is always accompanied by the color deformation, it is not sufficient to use the shape invariant or color invariant descriptors only and the use of combined invariants is needed. However, the SCAMIs are not able to recognize images, the color channels of which are linearly dependent or highly correlated. This situation is not rare in practice and is of particular importance in hyper-spectral image analysis, where the spectral bands are highly correlated. We analyze why the SCAMIs fail in such situations, correct the theory and propose a solution to overcome such drawback. Unlike the SCAMIs, the new invariants have in the null-space the constant-zero images only, which leads to a better discrimination power, as demonstrated also on various pictures.

Název v anglickém jazyce

On the Null-Space of the Shape-Color Moment Invariants

Popis výsledku anglicky

In this paper, we extend the theory of the combined Shape-Color Affine Moment Invariants (SCAMIs) for recognition of color images, proposed originally by Gong et al. in [3]. Since in the real pictures the shape deformation is always accompanied by the color deformation, it is not sufficient to use the shape invariant or color invariant descriptors only and the use of combined invariants is needed. However, the SCAMIs are not able to recognize images, the color channels of which are linearly dependent or highly correlated. This situation is not rare in practice and is of particular importance in hyper-spectral image analysis, where the spectral bands are highly correlated. We analyze why the SCAMIs fail in such situations, correct the theory and propose a solution to overcome such drawback. Unlike the SCAMIs, the new invariants have in the null-space the constant-zero images only, which leads to a better discrimination power, as demonstrated also on various pictures.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20206 - Computer hardware and architecture

Projekt

<a href="/cs/project/GA18-07247S" target="_blank" >GA18-07247S: Metody a algoritmy pro analýzu obrazů vektorových a tenzorových polí</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

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 : CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings

ISBN

978-3-030-29929-3

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

402-408

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Salerno

Datum konání akce

2. 9. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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