Real-time monitoring of optimum timing for harvesting fresh tea leaves based on machine vision

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成果类型：

期刊论文

作者：

Zhang, Liang;Zhang, Hongduo;Chen, Yedong;Dai, Sihui;Li, Xumeng*;...

通讯作者：

Li, Ming;Li, Xumeng

作者机构：

[Li, Ming; Zhang, Liang; Chen, Yedong; Zhang, Hongduo] Hunan Agr Univ, Coll Engn, Changsha 410128, Hunan, Peoples R China.

[Liu, Zhonghua; Dai, Sihui] Hunan Agr Univ, Coll Hort & Landscape, Changsha 410128, Hunan, Peoples R China.

[Li, Xumeng] Hunan Agr Univ, Coll Agr, Changsha 410128, Hunan, Peoples R China.

[Imou, Kenji] Univ Tokyo, Grad Sch Agr & Life Sci, Dept Biol & Environm Engn, Tokyo 1130033, Japan.

[Li, Ming] Shandong Univ Technol, Sch Agr Engn & Food Sci, Zibo 255000, Peoples R China.

通讯机构：

[Li, Ming; Li, Xumeng] H

Hunan Agr Univ, Coll Engn, Changsha 410128, Hunan, Peoples R China.

Hunan Agr Univ, Coll Agr, Changsha 410128, Hunan, Peoples R China.

语种：

英文

关键词：

Agricultural machinery;Fresh tea leaves;Intelligent recognition;Machine vision;Real-time monitoring

期刊：

国际农业与生物工程学报(英文)

ISSN：

1934-6344

年：

2019

卷：

期：

页码：

6-9

DOI：

10.25165/j.ijabe.20191201.3418

基金类别：

2018YFD0200803

机构署名：

本校为第一且通讯机构

院系归属：

农学院

园艺园林学院

工学院

摘要：

The harvesting time of fresh tea leaves has a significant impact on product yield and quality. The aim of this study was to propose a method for real-time monitoring based on machine vision to determine the optimum harvesting time for picking fresh tea leaves. Firstly, the shapes of fresh tea leaves were distinguished from RGB images of the tea-tree canopy after graying with the improved B-G algorithm, filtering with a median filter algorithm, binary processing with the Otsu algorithm, and noise reduction and edge smoothing using open and close...

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Real-time monitoring of optimum timing for harvesting fresh tea leaves based on machine vision

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