检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:何杨帆 汪焕悦 张君 刘传峰 孙磊[1] 索雪松[1] 范晓飞 HE Yangfan;WANG Huanyue;ZHANG Jun;LIU Chuanfeng;SUN Lei;SUO Xuesong;FAN Xiaofei(College of Mechanical and Electrical Engineering,Hebei Agricultural University,Baoding 071001,China;College of Information Science and Technology,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 [2]河北农业大学信息科学与技术学院,河北保定071001
出 处:《河北农业大学学报》2024年第6期69-74,共6页Journal of Hebei Agricultural University
基 金:国家自然科学基金项目(32070572,32202474);河北省高层次人才资助项目(E2019100006);河北农业大学引进人才项目(YJ201847)。
摘 要:为解决目前人工鉴定大白菜叶色主观性强、速度慢、效率低等问题,本研究提出了一种多光谱图像处理结合机器视觉技术对大白菜叶色快速、准确分类和量化的方法。结果表明:由19通道多光谱系统提取到的原始光谱数据包含信息更全面更准确,由其所建立的SVM分类模型具有最优的分类效果,训练集准确率是98.24%,验证集准确率是87.18%。运用连续投影算法(SPA)提取特征波长进行分析,选择用5通道相机采集的白菜样本继续研究大白菜叶色的量化。通过提取其RGB、HSV、LAB 9个颜色特征值进行数据处理后可以准确地将大白菜叶色进行0~100间数值量化。In order to solve the problems of strong subjectivity,slow speed and low efficiency in manual identification of leaf color of Chinese cabbage,this study proposed a method of rapid and accurate classification and quantification of leaf color of Chinese cabbage by combining multi-spectral image processing with machine vision technology.The results showed that the original spectral data extracted by the 19-channel multispectral system contained more comprehensive and accurate information,and the SVM classification model established by the system showed the best classification effect.The accuracy of training set was 98.24%,and the accuracy of verification set was 87.18%.The continuous projection algorithm(SPA)was used to extract characteristic wavelength for analysis,and the Chinese cabbage samples collected by a 5-channel camera were selected to continue to continuously study the quantification of leaf color of Chinese cabbage.By extracting the RGB,HSV,LAB nine color feature values for data processing,the color of Chinese cabbage leaves can be accurately quantized by 0-100 values.
分 类 号:S24[农业科学—农业电气化与自动化]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.249