返回
Olive fly sting detection based on computer vision
DOI:10.1016/j.postharvbio.2019.01.003.png)
摘要
En 中文
Olive fly (Bactrocera oleae Rossi) is a parasite that infects olive fruit by stinging the fruit to deposit its eggs. The infection damages the fruit during its growth and affects the quality of the olive oil as a final product. Detection of olive fly stings in the virgin olive oil production process is therefore critical. This research aimed to develop automatic methodologies based on computer vision to detect fly stings in infected olive fruit samples. Different methodologies to detect defective areas on the surface of the fruit and classify them between stings and other bruises are described. The methodology to detect defective areas reached a success ratio of 93% and best classification algorithms reached a success ratio close to 80%. The proposed methodology could be applied at reception of fruit for input of the virgin olive oil production process.
Keyword:
Olive fruit
Olea europaea
Olive fly
Bactrocera oleae
Olive fly sting
Image processing
Computer vision
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.8
论文数:
6.7K
被引数:
2.6W
机构
引用论文
A Hybrid Agent-based Design Methodology for Dynamic Cross-layer Reliability in Heterogeneous Embedded Systems异构嵌入式系统中基于混合代理的动态跨层可靠性设计方法
Economic benefit evaluation method for the micro-grid renewable energy system operation微网可再生能源系统运行经济效益评价方法
The intelligent prediction of membrane fouling during membrane filtration by mathematical models and artificial intelligence models
Chemosphere
IF0
Identification of leaf volatiles from olive (Olea europaea) and their possible role in the ovipositional preferences of olive fly, Bactrocera oleae (Rossi) (Diptera: Tephritidae)
PHYTOCHEMISTRY
IF3.4

