Publication details

Rotationally Invariant Bark Recognition

Conference Paper (international conference)

Remeš Václav, Haindl Michal


serial: Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, p. 22-31 , Eds: Bai X., Hancock E., Ho T., Wilson R., Biggio B., Robles-Kelly A.

action: IAPR Joint International Workshop on Statistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition, (Beijing, CN, 20180817)

keywords: Bark recognition, Tree taxonomy clasification, Spiral Markov random field model

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abstract (eng):

An efficient bark recognition method based on a novel wide-sense Markov spiral model textural representation is presented. 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 method significantly outperforms the state-of-the-art bark recognition approaches in terms of the classification accuracy.

RIV: BD