bibtype J - Journal Article
ARLID 0452147
utime 20240103211405.4
mtime 20151208235959.9
WOS 000366844400011
SCOPUS 84949479880
DOI 10.1016/j.patrec.2015.10.012
title (primary) (eng) Robust histogram-based image retrieval
specification
page_count 10 s.
media_type P
serial
ARLID cav_un_epca*0257389
ISSN 0167-8655
title Pattern Recognition Letters
volume_id 69
volume 1 (2016)
page_num 72-81
publisher
name Elsevier
keyword Image retrieval
keyword Noisy image
keyword Histogram
keyword Convolution
keyword Moments
keyword Invariants
author (primary)
ARLID cav_un_auth*0282545
name1 Höschl
name2 Cyril
full_dept (cz) Zpracování obrazové informace
full_dept (eng) Department of Image Processing
department (cz) ZOI
department (eng) ZOI
institution UTIA-B
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101087
name1 Flusser
name2 Jan
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
institution UTIA-B
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2015/ZOI/hoschl-0452147.pdf
cas_special
project
project_id GA15-16928S
agency GA ČR
ARLID cav_un_auth*0314467
abstract (eng) We present a histogram-based image retrieval method which is designed specifically for noisy query images. The images are reretrieved according to histogram similarity. To reach high robustness to noise, the histograms are described by newly proposed features which are insensitive to a Gaussian additive noise in the original images. The advantage of the new method is proved theoretically and demonstrated experimentally on real data.
reportyear 2016
RIV JD
num_of_auth 2
mrcbC52 4 A hod 4ah 20231122141346.5
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0253176
mrcbC64 1 Department of Image Processing UTIA-B 10200 COMPUTER SCIENCE, THEORY & METHODS
confidential S
mrcbC86 2 Article Computer Science Artificial Intelligence
mrcbT16-e COMPUTERSCIENCEARTIFICIALINTELLIGENCE
mrcbT16-j 0.662
mrcbT16-s 0.729
mrcbT16-4 Q1
mrcbT16-B 56.615
mrcbT16-D Q2
mrcbT16-E Q2
arlyear 2016
mrcbTft \nSoubory v repozitáři: hoschl-0452147.pdf
mrcbU14 84949479880 SCOPUS
mrcbU34 000366844400011 WOS
mrcbU63 cav_un_epca*0257389 Pattern Recognition Letters 0167-8655 1872-7344 Roč. 69 č. 1 2016 72 81 Elsevier