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Zhang, F., Sun, H., Xie, S., Dong, C., Li, Y., Xu, Y., et al. (2023) A Tea Bud Segmentation, Detection and Picking Point Localization Based on the MDY7-3PTB Model. Frontiers in Plant Science, 14, Article 1199473.
https://doi.org/10.3389/fpls.2023.1199473

has been cited by the following article:

• TITLE: Tea Image Recognition and Research on Structure of Tea Picking End-Effector

  AUTHORS: Biao Huang, Shiping Zou

  KEYWORDS: Image Recognition of Tea Leaves, Tea Picking End-Effector, Tea PickingStructure Design

  JOURNAL NAME: Journal of Electronics Cooling and Thermal Control, Vol.13 No.3, September 30, 2024

  ABSTRACT: The automated picking technology of tea is an important part of the development of smart agriculture, which affects the development of the tea industry to a certain extent. Tea leaf recognition and robotic tea picking end-effector are the key technologies for automated tea picking. This paper proposes a set of algorithms for tea leaf differentiation and recognition based on the principle of colour difference. And on the basis of this algorithm, a tea picking end-effector is designed. The experiments show that the designed tea picking end-effector has good recognition ability and high tea picking speed.