目的 为快速准确地鉴别多品牌卷烟真伪，提出一种基于视觉词袋模型提取烟盒胶痕图像特征的鉴别方法。方法 首先，利用自主设计的多光源胶痕采集装置获取烟盒内部的胶痕图像，通过图像处理技术去除原始图像的部分背景后得到胶痕图像样本;然后，从胶痕图像样本中提取尺度不变特征转换(SIFT)特征，并用K-Means算法对特征聚类生成视觉词典;再依据视觉词典的视觉单词直方图特征集对胶痕图像进行训练分类，从而达到鉴别卷烟真伪的目的。结果 以10种真品包装机型生产的烟盒胶痕图像以及假冒烟盒胶痕图像为对象，烟盒样品涉及64个卷烟品牌，对360张胶痕图像分类测试，得到真伪识别率为97.22%，每个样本平均鉴别时间为0.05 s。结论 提出的方法采集胶痕图像简便、真伪鉴别效率和准确率高，并适用于多种卷烟品牌。为提高真伪卷烟鉴别效率、准确率和通用性提供了技术支持。

The work aims to propose a method based on visual word bag model to extract the features of plastic marks in cigarette packets to quickly and accurately identify the authenticity of multi-brand cigarettes. Firstly, a self-designed multi-light source glue mark acquisition device was used to obtain the glue mark image inside the cigarette packet, and the glue mark image sample was obtained after removing part of the background of the original image by image processing technology. Then, scale invariant Feature conversion (SIFT) features were extracted from the glue mark image samples, and K-Means algorithm was used to cluster the features to generate a visual dictionary. Then, according to the visual word histogram feature set of the visual dictionary, the glue mark images were trained and classified, so as to identify the authenticity of cigarette. In this paper, 10 samples of authentic cigarette packets and counterfeit cigarette packets of 64 cigarette brands were taken as the objects. The classification test of 360 cigarette packet images showed that the authenticity recognition rate was 97.22%, and the average identification time of each sample was less than 0.05 s. The above method is simple to collect glue marks, has high authenticity identification efficiency and accuracy, and is suitable for a variety of cigarette brands. It provides technical support for improving the efficiency, accuracy and universality of authenticity identification.