基于多光谱的玉米种子外观质量检测方法  

Detection method of maize seed appearance quality based on multi-spectrum

作　　者：宋畅 彭勃 范晓飞 SONG Chang;PENG Bo;FAN Xiaofei(College of Mechanical and Electrical Engineering,Hebei Agricultural University,Baoding 071001,China)

机构地区：[1]河北农业大学机电工程学院,河北保定071001

出　　处：《河北农业大学学报》2024年第6期83-88,共6页Journal of Hebei Agricultural University

基　　金：国家大宗蔬菜产业技术体系(CARS-23);国家自然科学基金(32072572);河北农业大学人才引进研究项目(YJ201847);河北省省属高等学校基本科研业务费研究项目(KY2022019).

摘　　要：缺陷种子显著影响种子品质及定价,其分选剔除是种子质量检测的重要工作环节。目前种子的质量检测主要由人工操作完成,效率低且具有主观性。针对玉米种子在外观质量检测中需要快速、精准识别的需求,本文提出以玉米种子多光谱RGB+NIR+NIR1的成像信息做输入的改进型YOLOv5目标检测模型,对玉米种子外观质量进行识别与分类。通过在YOLOv5主干网络CSPDarknet中改用串行空间金字塔池化结构(Spatial pyramid pooling,SPP),提升网络模型检测效率,在加强特征提取网络中利用注意力机制强化特征信息融合,提升网络模型检测精度。试验结果表明改进模型YOLOv5+SE+SPPF的综合评价指标F1值达到了96.71%,mAP值达到了96.96%,平均每检测一张图像耗时约0.28 s,平均每检测一粒种子耗时约20 ms,为实现种子高效、精准地质量检测和优选分级提供了参考,可实际应用于种子智能化分选装备。Defective seeds significantly affect seed quality and pricing,and their sorting and removal is an important part of seed quality detection.At present,the seed quality detection is mainly completed by manual operation,which is inefficient and subjective.Aiming at the need for rapid and accurate identification of corn seeds in appearance quality detection,this paper proposed an improved YOLOv5 target detection model with input of multi-spectral RGB+NIR+NIR1 imaging information of corn seeds to identify and classify appearance quality of corn seeds.By changing the Spatial pyramid pooling(SPP)structure in the YOLOv5 backbone network CSPDarknet,the efficiency of network model detection was improved,and the attention mechanism was used to strengthen the feature information fusion in the feature extraction network to improve the accuracy of network model detection.The test results showed that the comprehensive evaluation index F1 value of the improved model YOLOv5+SE+SPPF reached 96.71%,the mAP value reached 96.96%,the average time for each image detection was about 0.28 s,and the average time for each seed detection was about 20 ms,which provided a reference for achieving efficient and accurate seed quality detection and optimal grading,and can be applied to the intelligent seed sorting equipment.

关 键 词：玉米种子 外观质量 多光谱成像 YOLOv5 注意力机制 

分 类 号：S24[农业科学—农业电气化与自动化]