TY - GEN
T1 - Research on branch reconstruction method based on branch growth characteristics for apple picking
AU - Song, Gengyang
AU - Song, Huatao
AU - Dong, Xia
AU - Xu, Haibo
N1 - Publisher Copyright:
© 2024 SPIE.
PY - 2024
Y1 - 2024
N2 - During the operation of apple picking robots, it is necessary to accurately identify branches to prevent collisions with them. However, obtaining branch images in complex environments is often fragmented, making it difficult to reconstruct the entire tree. To solve this problem, this study obtained branch images by removing non-branch areas, and extract tree skeletons and endpoints based on 8-connection and thin line methods. This study investigates the growth characteristics of fruit tree branches and the distribution of endpoints between branches at the same level, using this as a constraint to connect broken branches. Finally, the reconstruction of the entire tree is achieved. The experimental results show that the algorithm has a branch recognition rate of 92.1% on sunny days and 84.2% on cloudy days. Therefore, the algorithm proposed in this study can provide accurate branch information for apple picking robots.
AB - During the operation of apple picking robots, it is necessary to accurately identify branches to prevent collisions with them. However, obtaining branch images in complex environments is often fragmented, making it difficult to reconstruct the entire tree. To solve this problem, this study obtained branch images by removing non-branch areas, and extract tree skeletons and endpoints based on 8-connection and thin line methods. This study investigates the growth characteristics of fruit tree branches and the distribution of endpoints between branches at the same level, using this as a constraint to connect broken branches. Finally, the reconstruction of the entire tree is achieved. The experimental results show that the algorithm has a branch recognition rate of 92.1% on sunny days and 84.2% on cloudy days. Therefore, the algorithm proposed in this study can provide accurate branch information for apple picking robots.
KW - 8-connection
KW - Branch reconstruction
KW - apple picking
KW - growth characteristics
KW - thin line method
UR - https://www.scopus.com/pages/publications/85201971314
U2 - 10.1117/12.3037935
DO - 10.1117/12.3037935
M3 - 会议稿件
AN - SCOPUS:85201971314
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering, AEMCSE 2024
A2 - Yang, Lvqing
PB - SPIE
T2 - 7th International Conference on Advanced Electronic Materials, Computers, and Software Engineering, AEMCSE 2024
Y2 - 10 May 2024 through 12 May 2024
ER -