浆果
鲜食葡萄
自动化
表(数据库)
人工智能
稀释
领域(数学)
计算机科学
计算机视觉
数学
工程类
园艺
地理
机械工程
数据挖掘
纯数学
林业
生物
作者
Yan San Woo,Zhuguang Li,Shun Tamura,Prawit Buayai,Hiromitsu Nishizaki,Koji Makino,Latifah Munirah Kamarudin,Xiaoyang Mao
标识
DOI:10.1016/j.compag.2023.108328
摘要
A crucial step in the production of table grapes is berry thinning. This is because the market value of table grape production is significantly influenced by bunch compactness, bunch form and berry size, all of which are primarily regulated by this task. Grape farmers must count the number of berries in the working bunch and decide which berry should be eliminated during thinning, a process requiring extensive viticultural knowledge. However, the use of 2D pictures for automatic berry counting and identifying the berries to be removed has limitations, as the number of visible berries might vary greatly depending on the direction of view. In addition, it is extremely important to understand the 3D structure of a bunch when considering future automation via robotics. For the reasons stated, obtaining a field-applicable 3D grape bunch model is needed. Thus, the contribution of this study is a novel technology for reconstructing a 3D model of a grape bunch with uniquely identified berries from 2D images captured in the real grape field environment.
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