基于无人机RGB影像的棉花苗期株数提取研究

doi:10.13733/j.jcam.issn.2095-5553.2024.10.039

摘要/Abstract

摘要： 快速、准确、大范围地获取棉花苗期株数对于棉花早期育种决策以及实现棉田的精准管理起着至关重要的作用。针对棉花苗期田间存在盖地膜等干扰易对株数提取造成影响，提出一种基于过红指数和超绿指数，结合图像处理方法对无人机RGB影像进行棉花株数统计的方法。利用新疆阿克苏地区阿瓦提县的棉田无人机影像进行研究，对采集到的数据进行预处理、超绿指数（ExG）和过红指数（ExR）计算、Otsu阈值分割等处理，经处理后的二值图像噪点以及盖地膜产生的误分类像选择采用Majority分析处理进行去噪，其中对Majority分析中的3×3、5×5、7×7、9×9不同大小的变换核的去噪效果进行对比分析，实现对棉花苗期株数的提取。经试验得出在过红指数9×9变换核处理下棉花株数提取效果最好，统计的株数准确率达到97.84%。超绿指数在不同大小的变换核处理后的棉花株数统计准确率都在95%以上，其中基于5×5变换核提取的棉花株数准确率达到98.86%。本方法不仅能够提高棉花株数统计的准确性，也可为棉田早期育种，精准管理提供技术支撑。

关键词: 棉花育种, 棉田精准管理, 棉花株数, 过红指数, 超绿指数, 阈值分割

Abstract: Rapid, accurate and large‑scale acquisition of cotton seedlings number plays a vital role in the decision‑making of early cotton breeding and the realization of precise management of cotton fields. Aiming at the interference of mulching film and other disturbances in the field of cotton seedlings, which can easily affect the extraction of plant numbers, this paper proposes a method based on the over‑red index and ultra‑green index, combined with image processing methods for counting the number of cotton plants in UAV RGB images. This article uses the UAV images of cotton fields in Awati County, Aksu Prefecture, Xinjiang to conduct research, and preprocesses the collected data, and calculates the Excess green index (ExG) and Excess red index (ExR), Otsu threshold segmentation and other processing, and then the processed binary image noise and misclassified images generated by the mulch film are selected to use Majority analysis processing for denoising, among which, the denoising effect of 3×3、 5×5、 7×7、 9×9 transformation kernels with different sizes in the Majority analysis is compared and analyzed, and finally the the number of cotton seedlings is extracted. The experiment shows that the extraction effect of cotton plant number is the best under the redness index 9×9 conversion kernel treatment, and the accuracy rate of statistical plant number reaches 97.84%. The statistical accuracy rate of the super green index for the number of cotton plants after different sizes of transformed kernels is above 95%, and the accuracy rate of cotton plant numbers extracted based on the 5×5 transformed kernels reaches 98.86%. The results show that this method can not only improve the accuracy of counting the number of cotton plants, but also provide technical support for early breeding and precise management of cotton fields.

Key words: cotton breeding, cotton field precise management, number of cotton plants, Excess red index, Excess green index, threshold segmentation

中图分类号:

S252

阳光, 李晓娟, 梁治, 刘博. 基于无人机RGB影像的棉花苗期株数提取研究[J]. 中国农机化学报, 2024, 45(10): 269-273.

Yang Guang, Li Xiaojuan, Liang Zhi, Liu Bo. Research on extraction of cotton seedling plant number based on UAV RGB image[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(10): 269-273.

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