Bark recognition using novel rotationally invariant multispectral textural features
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00506602" target="_blank" >RIV/67985556:_____/19:00506602 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0167865519301886" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0167865519301886</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.patrec.2019.06.027" target="_blank" >10.1016/j.patrec.2019.06.027</a>
Alternative languages
Result language
angličtina
Original language name
Bark recognition using novel rotationally invariant multispectral textural features
Original language description
We present novel rotationally invariant fully multispectral Markovian textural features applied for the efficient tree bark recognition. These textural features are derived from the novel descriptive multispectral spiral wide-sense Markov model. Unlike the alternative bark recognition methods based on various gray-scale discriminative textural descriptions, we benefit from fully descriptive color, rotationally invariant bark texture representation. The proposed methods significantly outperform the state-of-the-art bark recognition approaches regarding classification accuracy. Both our classifiers outperform convolutional neural network ResNet even on the largest public bark database BarkNet which contains 23 000 high-resolution images from 23 different tree species.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20202 - Communication engineering and 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
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Pattern Recognition Letters
ISSN
0167-8655
e-ISSN
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Volume of the periodical
125
Issue of the periodical within the volume
1
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
6
Pages from-to
612-617
UT code for WoS article
000482374500084
EID of the result in the Scopus database
2-s2.0-85068558335