Key technology of crop precision sowing based on vision principle

IF 2.4 4区 农林科学 Q2 AGRICULTURAL ENGINEERING
Bing-chuan Li, Jiyun Li
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引用次数: 0

Abstract

In the process of precision planting of crops, due to many external environmental interference factors, low precision of sowing technology and large relative errors, the growth of crops is seriously affected. To solve this problem, machine vision technology is introduced to study the key technology of crop precision sowing based on vision principle. After preprocessing the crop image, the corresponding histogram is established. The segmentation threshold method is used to gray the image and determine the best threshold, so that the image has a good recognition effect. According to the growth height and color analysis of crops in the image, predict the growth of crops and realize the precision sowing of crops. The comparative experimental results show that under the application of the new sowing technology, the estimation accuracy of crop planting area is high, the recognition accuracy of planting position is also high, and the fertilization uniformity is close to the actual data, which can provide an important basis for improving the quality of crop sowing.
基于视觉原理的作物精准播种关键技术
在作物精准种植过程中,由于外界环境干扰因素多,播种技术精度低,相对误差大,严重影响了作物的生长。为解决这一问题,引入机器视觉技术,研究基于视觉原理的作物精准播种关键技术。对裁剪图像进行预处理后,建立相应的直方图。采用分割阈值法对图像进行灰度化处理,确定最佳阈值,使图像具有良好的识别效果。根据图像中作物的生长高度和颜色分析,预测作物的生长情况,实现作物的精准播种。对比试验结果表明,在新播种技术应用下,作物种植面积估算精度高,种植位置识别精度也高,施肥均匀度接近实际数据,可为提高作物播种质量提供重要依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Agricultural Engineering
Journal of Agricultural Engineering AGRICULTURAL ENGINEERING-
CiteScore
2.30
自引率
5.60%
发文量
40
审稿时长
10 weeks
期刊介绍: The Journal of Agricultural Engineering (JAE) is the official journal of the Italian Society of Agricultural Engineering supported by University of Bologna, Italy. The subject matter covers a complete and interdisciplinary range of research in engineering for agriculture and biosystems.
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