Kernel-mapped Histograms of Multi-scale LBPs for Tree Bark Recognition

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00211358" target="_blank" >RIV/68407700:21230/13:00211358 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/IVCNZ.2013.6726996" target="_blank" >http://dx.doi.org/10.1109/IVCNZ.2013.6726996</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IVCNZ.2013.6726996" target="_blank" >10.1109/IVCNZ.2013.6726996</a>

Result language
angličtina
Original language name
Kernel-mapped Histograms of Multi-scale LBPs for Tree Bark Recognition
Original language description
We propose a novel method for tree bark identification by SVM classification of feature-mapped multi-scale descriptors formed by concatenated histograms of Local Binary Patterns (LBPs). A feature map approximating the histogram intersection kernel significantly improves the methods accuracy. Contrary to common practice, we use the full 256 bin LBP histogram rather than the standard 59 bin histogram of uniform LBPs and obtain superior results. Robustness to scale changes is handled by forming multiple multi-scale descriptors. Experiments conducted on a standard dataset show 96.5% accuracy using ten-fold cross validation. Using the standard 15 training examples per class, the proposed method achieves a recognition rate of 82.5% and significantly outperforms both the state-of-the-art automatic recognition rate of 64.2% and human experts with recognition rates of 56.6% and 77.8%. Experiments on standard texture datasets confirm that the proposed method is suitable for general texture recog
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
28th International Conference of Image and Vision Computing New Zealand (IVCNZ 2013)
ISBN
978-1-4799-0882-0
ISSN
2151-2191
e-ISSN
—
Number of pages
6
Pages from-to
82-87
Publisher name
IEEE
Place of publication
Piscataway
Event location
Wellington
Event date
Nov 27, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)