期刊
COMPUTERS AND ELECTRONICS IN AGRICULTURE
卷 116, 期 -, 页码 8-19出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compag.2015.05.021
关键词
Machine vision; Fruit detection; Fruit localization; Robotic harvesting; Crop-load estimation; Specialty crops
资金
- Washington Tree Fruit Research Commission
- Washington State University Agricultural Research Center federal formula funds [WNP0745]
- U.S. Department of Agriculture National Institutes for Food and Agriculture (NIFA) [WNP0728]
- Washington State University Irrigated Agriculture Research and Extension Center
This paper reviews the research and development of machine vision systems for fruit detection and localization for robotic harvesting and/or crop-load estimation of specialty tree crops including apples, pears, and citrus. Variable lighting condition, occlusions, and clustering are some of the important issues needed to be addressed for accurate detection and localization of fruit in orchard environment. To address these issues, various techniques have been investigated using different types of sensors and their combinations as well as with different image processing techniques. This paper summarizes various techniques and their advantages and disadvantages in detecting fruit in plant or tree canopies. The paper also summarizes the sensors and systems developed and used by researchers to localize fruit as well as the potential and limitations of those systems. Finally, major challenges for the successful application of machine vision system for robotic fruit harvesting and crop-load estimation, and potential future directions for research and development are discussed. (C) 2015 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据