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基于特征点配准的真伪卷烟商标纸鉴别

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为提高真伪卷烟商标纸鉴别的准确性和效率,降低鉴别的经验要求和主观性,提出一种基于特征点配准的真伪卷烟商标纸鉴别方法。使用一致的标准扫描采集卷烟样品图像,基于尺度不变特征转换算法提取图像特征点,通过特征匹配和基于单应性变换的图像配准获取判别预测变量。采用逻辑回归、梯度提升分类决策树算法构建二元分类模型对图像样本进行训练和评估。在64个卷烟规格、2 918个样本数据集上进行实验,该方法准确率高于95%。通过对比实验验证了该方法的稳定性和有效性。
IDENTIFICATION OF GENUINE AND FAKE CIGARETTE PACK LABEL BASED ON FEATURE POINT REGISTRATION
In order to improve the accuracy and efficiency of the identification of genuine and fake cigarette label paper,and reduce the experience requirements and subjectivity of identification,this paper proposes a method for identifying cigarette label paper based on feature point registration.Sample images were acquired based on a unified image acquisition standard,and discriminant predictors were acquired through feature point extraction and description based on SIFT algorithm,feature matching and image registration based on homograph transformation.Logistic regression algorithm and gradient boosting classification decision tree algorithm were selected to construct a binary classification model for training and evaluation.We performed experimental evaluation on 64 cigarette specifications and 2918 sample data sets.The results show that the accuracy of the proposed identification method is higher than 95%.The stability and effectiveness of the proposed identification method are verified through a comparative experiment.

Cigarette label paperIdentification of genuine and fakeFeature pointImage registrationModel algorithmMachine Learning

冯伟华、王锐、宗国浩、赵志成、罗泽、周明珠、李晓辉、邢军

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中国烟草总公司郑州烟草研究院 河南郑州 450001

中国科学院计算机网络信息中心 北京 100190

中国科学院大学 北京 100049

中国烟草总公司国家烟草质量监督检验中心 河南郑州 450001

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卷烟商标纸 真伪鉴别 特征点 图像配准 模型算法 机器学习

国家烟草专卖局科技重大专项

110201901029SJ-08

2024

计算机应用与软件
上海市计算技术研究所 上海计算机软件技术开发中心

计算机应用与软件

CSTPCD北大核心
影响因子:0.615
ISSN:1000-386X
年,卷(期):2024.41(3)
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