An Ensemble Template Algorithm for Extracting Targets from Blurred Infrared Images

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU107003" target="_blank" >RIV/00216305:26220/14:PU107003 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ijleo.2013.07.130" target="_blank" >http://dx.doi.org/10.1016/j.ijleo.2013.07.130</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ijleo.2013.07.130" target="_blank" >10.1016/j.ijleo.2013.07.130</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An Ensemble Template Algorithm for Extracting Targets from Blurred Infrared Images

Popis výsledku v původním jazyce

In this paper, an ensemble template algorithm is proposed to extract targets from blurred infrared images. First, the image pixels are divided according to their grey values into three pixel sets, a target set, a background set and the third set without class label. Second, the neighbourhood statistical characteristics for each pixel are calculated as its template features. Third, ensemble detectors are designed using target pixels and background pixels based on their template features, and these ensemble detectors are used to detect the third pixel set. To evaluate the performance of the proposed extraction algorithm, this paper compares the ensemble template with other extraction algorithms using blurred infrared image of hand trace. Experimental results show that the ensemble template algorithm proposed in this paper exhibits better extraction performance.

Název v anglickém jazyce

An Ensemble Template Algorithm for Extracting Targets from Blurred Infrared Images

Popis výsledku anglicky

In this paper, an ensemble template algorithm is proposed to extract targets from blurred infrared images. First, the image pixels are divided according to their grey values into three pixel sets, a target set, a background set and the third set without class label. Second, the neighbourhood statistical characteristics for each pixel are calculated as its template features. Third, ensemble detectors are designed using target pixels and background pixels based on their template features, and these ensemble detectors are used to detect the third pixel set. To evaluate the performance of the proposed extraction algorithm, this paper compares the ensemble template with other extraction algorithms using blurred infrared image of hand trace. Experimental results show that the ensemble template algorithm proposed in this paper exhibits better extraction performance.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název periodika

OPTIK

ISSN

0030-4026

e-ISSN

—

Svazek periodika

125

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

4

Strana od-do

954-957

Kód UT WoS článku

000329377400013

EID výsledku v databázi Scopus

2-s2.0-84889091782