河南农业科学 ›› 2022, Vol. 51 ›› Issue (3): 12-19.DOI: 10.15933/j.cnki.1004-3268.2022.03.002
刁智华,闫娇楠,赵素娜,贺振东
收稿日期:
2021-08-13
出版日期:
2022-03-15
发布日期:
2022-05-20
作者简介:
刁智华(1982-),男,河南夏邑人,副教授,博士,主要从事农业机器人和精准施药方面的研究。E-mail:diaozhua@163.com
基金资助:
DIAO Zhihua,YAN Jiaonan,ZHAO Suna,HE Zhendong
Received:
2021-08-13
Published:
2022-03-15
Online:
2022-05-20
摘要: 可靠的作物行识别是智慧农业机器人可靠导航的基石,可以有效减少农业机器人对农作物的损伤。基于图像处理的传统作物行识别技术包括图像预处理、特征提取、作物行拟合。综述了Hough变换法、最小二乘法、垂直投影法等传统作物行识别方法,并对其他的传统作物行识别方法进行了总结。随着智慧农业的发展,深度学习在农业领域受到越来越多的关注。更好地采集图像的各种特征,并与农业机械有效结合是深度学习作物行识别与传统方法的不同。从上述2个方面,对国内外的作物行识别算法研究做了较为系统的分析,指出基于图像处理的作物行识别算法目前存在的问题,最后根据现在的研究状况对未来的研究方向做出展望。
中图分类号:
刁智华, 闫娇楠, 赵素娜, 贺振东. 基于图像处理的作物行识别算法研究进展[J]. 河南农业科学, 2022, 51(3): 12-19.
DIAO Zhihua, YAN Jiaonan, ZHAO Suna, HE Zhendong. Review of Crop Row Recognition Algorithms Based on Image Processing[J]. Journal of Henan Agricultural Sciences, 2022, 51(3): 12-19.
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