Open AccessResearch on the Application of Machine Vision in Tea Autonomous Picking
Author(s) -
Tian Jiang,
Honglin Zhu,
Wenjiang Liang,
Jingshan Chen,
Feijuan Wen,
Long Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1952/2/022063
Subject(s) - machine vision , computer science , artificial intelligence , segmentation , process (computing) , point (geometry) , computer vision , geometry , mathematics , operating system
As a non-destructive, real-time, fast, objective, and economical detection method, machine vision technology has been widely used in target recognition and positioning in various fields in recent years. Selective picking of tea buds is an important prerequisite for high-quality and efficient tea production. Autonomous picking of tea based on machine vision has become a research hotspot at home and abroad. At present, many scholars have studied the visual recognition and positioning methods in the process of intelligent tea picking, but the effect has not yet reached the actual picking requirements. In order to give everyone a comprehensive understanding of the existing research methods, this article systematically reviews the tea bud segmentation and bud picking point positioning methods based on machine vision technology, and prospects the application prospects and directions of machine vision technology in tea picking.