Blur Invariant Template Matching Using Projection onto Convex Sets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00508018" target="_blank" >RIV/67985556:_____/19:00508018 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-29888-3_28" target="_blank" >http://dx.doi.org/10.1007/978-3-030-29888-3_28</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-29888-3_28" target="_blank" >10.1007/978-3-030-29888-3_28</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Blur Invariant Template Matching Using Projection onto Convex Sets

Popis výsledku v původním jazyce

Blur is a common phenomenon in image acquisition that negatively influences recognition rate if blurred images are used as a query in template matching. Various blur-invariant features and measures were proposed in the literature, yet they are often derived under conditions that are difficult to satisfy in practise, for example, images with zero background or periodically repeating images and classes of blur that are closed under convolution.We propose a novel blur-invariant distance that puts no limitation on images and is invariant to any kind of blur as long as the blur has limited support, non-zero values and sums up to one. A template matching algorithm is then derived based on the blur-invariant distance, which projects query images on convex sets constructed around template images. The proposed method is easy to implement, it is robust to noise and blur size, and outperforms other competitors in this area.

Název v anglickém jazyce

Blur Invariant Template Matching Using Projection onto Convex Sets

Popis výsledku anglicky

Blur is a common phenomenon in image acquisition that negatively influences recognition rate if blurred images are used as a query in template matching. Various blur-invariant features and measures were proposed in the literature, yet they are often derived under conditions that are difficult to satisfy in practise, for example, images with zero background or periodically repeating images and classes of blur that are closed under convolution.We propose a novel blur-invariant distance that puts no limitation on images and is invariant to any kind of blur as long as the blur has limited support, non-zero values and sums up to one. A template matching algorithm is then derived based on the blur-invariant distance, which projects query images on convex sets constructed around template images. The proposed method is easy to implement, it is robust to noise and blur size, and outperforms other competitors in this area.

Druh

D - Stať ve sborníku

CEP obor

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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

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Počet stran výsledku

12

Strana od-do

351-362

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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