Share Email Print
cover

Proceedings Paper

CNN-based tree species identification from bark image
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

This paper proposes a convolutional neural network (CNN)-based tree species identification method from bark image. The proposed method uses the well-known CNN model. The difficulty of our problem is to use a special tree image in which a colorful tag is stick on the bark. The tag is irrelevant to the species. In order to recognize with CNN, it is necessary to extract a region (ROI) excluding the tag. Thus, this paper proposes a ROI extraction method. Extracted ROI is fed to CNN. We evaluated the proposed method with six tree species. We carried out the evaluation experiment with various conditions, and found an optimal condition for our problem.

Paper Details

Date Published: 6 May 2019
PDF: 6 pages
Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110693G (6 May 2019); doi: 10.1117/12.2524213
Show Author Affiliations
Junya Ido, Kyushu Institute of Technology (Japan)
Takeshi Saitoh, Kyushu Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 11069:
Tenth International Conference on Graphics and Image Processing (ICGIP 2018)
Chunming Li; Hui Yu; Zhigeng Pan; Yifei Pu, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray