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基于NIR高光谱成像技术的长枣虫眼无损检测

Non-destructive Detection of Insect Hole in Jujube Based on Near-infrared Hyperspectral Imaging

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摘要

为了研究快速识别虫眼枣与正常枣的有效方法, 利用特征波长主成分分析法结合波段比算法进行虫眼枣识别。首先, 利用NIR高光谱成像系统采集130个长枣(50个正常、80个虫眼枣)图像, 提取并分析不同类型长枣特征区域的平均光谱曲线, 对970~1 670 nm范围内的光谱数据进行主成分分析, 确定7个特征波长(990, 1 028, 1 109, 1 160, 1 231, 1 285, 1 464 nm)。然后, 对长枣图像做主成分分析, 选择PC2图像进行虫眼识别, 虫眼与正常枣的识别率分别为67.5%、100%。为了进一步提高虫眼枣的识别率, 采用波段比(R1231/R1109)对未识别的虫眼枣进行再次识别, 识别率提高到90%。结果表明, 基于NIR高光谱成像技术的检测方法对虫眼枣识别是可行的, 同时也为多光谱成像技术应用于在线检测长枣品质提供了理论依据。

Abstract

In order to study an effective method for quickly detecting the intact jujubes and insect hole jujubes, principal component analysis (PCA) on the optimal wavelengths combined with band ratio were applied to identify the insect hole jujubes. First, the hyperspectral images of jujube in the spectral region between 900 nm and 1 700 nm were acquired for 130 jujube samples (50 intact, 80 insect hole), and obtained region of interests (ROIs) as an average spectral of various jujubes, the wavelengths between 970 nm and 1 670 nm were analyzed and combined with PCA method to determine seven feature wavelengths (i.e. 990, 1 028, 1 109, 1 160, 1 231, 1 285, 1 464 nm). Next, the PCA method was performed again based on important wavelengths and the second principal component (PC2) was used to classify insect hole jujubes. The classification rate of insect hole jujubes and intact jujubes was 67.5%, 100%, respectively. To improve identification rate, band ratio (R1231/R1109) was utilized to distinguish the previously unidentified jujubes and the classification rate of insect hole jujubes was from 67.5% to 90%. The results show that the hyperspectral imaging technology can be used to effectively identify the insect hole jujubes, in the meantime, which can provide research basis for online detection of jujube quality using multispectral imaging technology.

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中图分类号:TN27

DOI:10.3788/fgxb20133411.1527

所属栏目:发光学应用及交叉前沿

基金项目:国家自然科学基金(31060233); 国家科技支撑计划(2012BAF07B06); 2011年度宁夏回族自治区科技攻关计划资助项目

收稿日期:2013-07-07

修改稿日期:2013-09-06

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作者单位    点击查看

吴龙国:宁夏大学 农学院, 宁夏 银川750021
何建国:宁夏大学 农学院, 宁夏 银川750021
刘贵珊:宁夏大学 农学院, 宁夏 银川750021
贺晓光:宁夏大学 农学院, 宁夏 银川750021
王伟:宁夏大学 物理电气信息学院, 宁夏 银川750021
王松磊:宁夏大学 农学院, 宁夏 银川750021
李丹:宁夏大学 农学院, 宁夏 银川750021

联系人作者:吴龙国(1046156215@qq.com)

备注:吴龙国(1988-), 男, 陕西人, 主要从事农产品无损检测方面的研究。

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引用该论文

WU Long-guo,HE Jian-guo,LIU Gui-shan,HE Xiao-guang,WANG Wei,WANG Song-lei,LI Dan. Non-destructive Detection of Insect Hole in Jujube Based on Near-infrared Hyperspectral Imaging[J]. Chinese Journal of Luminescence, 2013, 34(11): 1527-1532

吴龙国,何建国,刘贵珊,贺晓光,王伟,王松磊,李丹. 基于NIR高光谱成像技术的长枣虫眼无损检测[J]. 发光学报, 2013, 34(11): 1527-1532

被引情况

【1】刘 猛,申 思,王 楠. 可见-近红外高光谱图像技术快速鉴别激光打印墨粉. 发光学报, 2017, 38(5): 662-668

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