基于颜色特征的小麦抽穗扬花期麦穗识别计数*

doi:10.13733/j.jcam.issn.20955553.2021.11.15

中国农机化学报 ›› 2021, Vol. 42 ›› Issue (11): 97-102.DOI: 10.13733/j.jcam.issn.20955553.2021.11.15

基于颜色特征的小麦抽穗扬花期麦穗识别计数^*

刘东^1,2, 曹光乔¹, 李亦白¹, 陈聪¹

1.农业农村部南京农业机械化研究所,南京市,210014;
2.中国农业科学院研究生院,北京市,463000

收稿日期:2021-08-16 修回日期:2021-10-13 出版日期:2021-11-15 发布日期:2021-11-15
通讯作者: 曹光乔,1978年生,湖北宜昌人,博士,研究员,博导;研究方向为农业机械化与农村发展。E-mail: caoguangqiao@126.com
作者简介:刘东,1996年生,山东聊城人,硕士研究生;研究方向为农业机械化工程与农业信息管理。E-mail: 1462322077@qq.com
基金资助:
*国家重点研发计划子课题(2017YFD0700601—2);中国农业科学院科技创新工程(农科院办(2014)216号)

Recognition and counting of wheat ears at flowering stage of heading poplar based on color features

Liu Dong^1,2, Cao Guangqiao¹, Li Yibai¹, Chen Cong¹

1. Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing, 210014, China;
2. Graduate School of Chinese Academy of Agricultural Sciences, Beijing, 463000, China

Received:2021-08-16 Revised:2021-10-13 Online:2021-11-15 Published:2021-11-15

摘要/Abstract

摘要： 识别小麦抽穗扬花期抽穗情况,可用于指导后期水肥管理、病害防治和产量预测等。为实现准确、自动地麦穗计数,提出一种基于颜色特征的麦穗计数方法。抽穗扬花期小麦麦穗与叶片、茎秆颜色非常接近,常见颜色特征并不能有效分割麦穗,通过彩色直方图均衡化和红绿归一化差异指数对麦穗进行有效提取。针对图像中麦穗粘连问题,利用改进Harris角点检测算法分别对垂直拍摄和45°夹角拍摄的小麦图像进行验证。通过样本图像进行计数试验,准确率分别为96.06%和94.74%。结果表明,经均衡化处理后麦穗、叶片和茎秆出现明显颜色色差,可以利用颜色特征提取大田环境下抽穗扬花期麦穗图像;麦穗细化后进行骨架交点检测,可用于粘连麦穗的准确计数。

关键词: 麦穗, 抽穗扬花期, 颜色特征, 角点检测

Abstract: The identification of wheat heading at flowering stage can be used to guide the later water and fertilizer management, disease control, yield prediction and other aspects. In order to realize accurate and automatic ear counting, this paper proposes a new ear counting method based on color features. The color of wheat ear is very close to that of leaf and stem at heading flowering stage, and the common color features can not segment wheat ear effectively. In this paper, we extracted wheat ear effectively by color histogram equalization and red green normalized difference index. Aiming at the problem of wheat spike adhesion in the image, this paper uses the improved Harris corner detection algorithm to verify the wheat images taken at vertical angle and 45° angle respectively. Through the sample image counting experiment, the accuracy is 96.06% and 94.74% respectively. The results showed that there were obvious color differences in wheat ears, leaves and stems after equalization, and the color features could be used to extract the images of wheat ears at flowering stage in field environment. The detection of skeleton intersection point after wheat ear thinning can accurately count the conglutinated wheat ears with high counting accuracy, which can be used to reflect the situation of wheat heading in this period.

Key words: wheat ear, flowering date of poplar, color characteristics, corner detection

中图分类号:

TP391.4

刘东, 曹光乔, 李亦白, 陈聪. 基于颜色特征的小麦抽穗扬花期麦穗识别计数^*[J]. 中国农机化学报, 2021, 42(11): 97-102.

Liu Dong, Cao Guangqiao, Li Yibai, Chen Cong. Recognition and counting of wheat ears at flowering stage of heading poplar based on color features[J]. Journal of Chinese Agricultural Mechanization, 2021, 42(11): 97-102.

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基于颜色特征的小麦抽穗扬花期麦穗识别计数^*

Recognition and counting of wheat ears at flowering stage of heading poplar based on color features

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