Texture-Based Leaf Identification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00230202" target="_blank" >RIV/68407700:21230/15:00230202 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-16220-1_14" target="_blank" >http://dx.doi.org/10.1007/978-3-319-16220-1_14</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-16220-1_14" target="_blank" >10.1007/978-3-319-16220-1_14</a>

Result language
angličtina
Original language name
Texture-Based Leaf Identification
Original language description
A novel approach to visual leaf identification is proposed. A leaf is represented by a pair of local feature histograms, one computed from the leaf interior, the other from the border. The histogrammed local features are an improved version of a recentlyproposed rotation and scale invariant descriptor based on local binary patterns (LBPs). Describing the leaf with multi-scale histograms of rotationally invariant features derived from sign- and magnitude-LBP provides a desirable level of invariance. Therepresentation does not use colour. Using the same parameter settings in all experiments and standard evaluation protocols, the method outperforms the state-of-the-art on all tested leaf sets - the Austrian Federal Forests dataset, the Flavia dataset, the Foliage dataset, the Swedish dataset and the Middle European Woods dataset - achieving excellent recognition rates above 99%. Preliminary results on images from the north and south regions of France obtained from the LifeCLEF'14 Plant
Czech name
—
Czech description
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Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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