Bark Recognition to Improve Leaf-based Classification in Didactic Tree Species Identification

被引:6
作者
Bertrand, Sarah [1 ]
Cerutti, Guillaume [2 ]
Tougne, Laure [1 ]
机构
[1] Univ Lyon, LIRIS, F-69676 Lyon, France
[2] INRIA, Virtual Plants INRIA Team, Montpellier, France
来源
PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 4 | 2017年
关键词
Bark; Leaf; Tree Recognition; Smart-phone;
D O I
10.5220/0006108504350442
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a botanical approach for tree species classification through automatic bark analysis. The proposed method is based on specific descriptors inspired by the characterization keys used by botanists, from visual bark texture criteria. The descriptors and the recognition system are developed in order to run on a mobile device, without any network access. Our obtained results show a similar rate when compared to the state of the art in tree species identification from bark images with a small feature vector. Furthermore, we also demonstrate that the consideration of the bark identification significantly improves the performance of tree classification based on leaf only.
引用
收藏
页码:435 / 442
页数:8
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