Textural Features Sensitivity to Scale and Illumination Variations
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F22%3A00561404" target="_blank" >RIV/67985556:_____/22:00561404 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-16210-7_19" target="_blank" >http://dx.doi.org/10.1007/978-3-031-16210-7_19</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-16210-7_19" target="_blank" >10.1007/978-3-031-16210-7_19</a>
Alternative languages
Result language
angličtina
Original language name
Textural Features Sensitivity to Scale and Illumination Variations
Original language description
Visual scene recognition is predominantly based on visual textures representing an object's material properties. However, the single material texture varies in scale and illumination angles due to mapping an object's shape. We present a comparative study of the color histogram, Gabor, opponent Gabor, Local Binary Pattern (LBP), and wide-sense Markovian textural features concerning their sensitivity to simultaneous scale and illumination variations. Due to their application dominance, these textural features are selected from more than n50 published textural features. Markovian features are information preserving, and we demonstrate their superior performance for scale and illumination variable observation conditions over the standard alternative textural features. We bound the scale variation by double size, and illumination variation includes illumination spectra, acquisition devices, and 35 illumination directions spanned above a sample.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/GA19-12340S" target="_blank" >GA19-12340S: Surface material recognition under variable optical observation conditions</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Computational Collective Intelligence : 14th International Conference, ICCCI 2022
ISBN
978-3-031-16209-1
ISSN
1865-0929
e-ISSN
1865-0937
Number of pages
13
Pages from-to
237-249
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Hammamet
Event date
Sep 26, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000871953900019