Automatic tree species identification from natural bark image

Junya Ido; Takeshi Saitoh

doi:10.1117/12.2557187

3 January 2020 Automatic tree species identification from natural bark image

Junya Ido, Takeshi Saitoh

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 1137305 (2020) https://doi.org/10.1117/12.2557187
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

In this research, we are studying on image-based identification of trees species that we can see everywhere. In our previous study, we showed that convolutional neural network (CNN) can recognize tree species by using a region of interest (ROI) image of bark. However, the bark region is manually extracted from a natural bark image. This paper solves this problem using semantic segmentation, and proposes an automatic tree species identification from natural bark image. The proposed method was evaluated with the bark image dataset collected independently. We confirmed the effectiveness of the proposed method.

Citation Download Citation

Junya Ido and Takeshi Saitoh "Automatic tree species identification from natural bark image", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137305 (3 January 2020); https://doi.org/10.1117/12.2557187

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