基于DBNet与CRNN融合模型的卷烟激光码识别方法  

Cigarette Laser Code Recognition Method Based on DBNet and CRNN Fusion Model

作　　者：马琦 文钰栋 梁尚荣 王可[2] MA Qi;WEN Yudong;LIANG Shangrong;WANG Ke(Xianyang City Tobacco Company Liquan Sub Branch,Xianyang 713200,China;College of Information and Control Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,China)

机构地区：[1]咸阳市烟草公司礼泉分公司,陕西咸阳713200 [2]西安建筑科技大学信息与控制工程学院,陕西西安710055

出　　处：《计算机与现代化》2025年第4期96-102,共7页Computer and Modernization

摘　　要：卷烟激光码识别是烟草稽查工作的重要手段。针对烟码背景复杂导致检测识别率低的问题,本文提出一种基于DBNet与CRNN融合模型的烟码识别方法。首先采用DBNet模型对烟码区域进行检测,通过引入可微分二值化实现烟码的准确定位与提取;然后采用CRNN模型对经过定位和裁剪处理的烟码区域图像进行特征识别,通过结合VGG网络与深层Bi-LSTM网络,获取空间特征和时序特征实现烟码的识别。经过实验验证,融合模型的检测准确率为91.9%,识别准确率为83.4%,在移动端APP部署后的测试准确率为83.0%,这表明本文方法能够提供精确的烟码识别效果。Cigarette laser code recognition is an important means of tobacco inspection work.Aiming at the problem of low detection and recognition rate due to the complex background of cigarette code,this paper proposes a cigarette code recognition method based on DBNet and CRNN.First,the DBNet model is used to detect the smoke code region,and the accurate positioning and extraction of the cigarette code is realized by introducing differentiable binarization.Then,the CRNN model is used to identify the features of the cigarette code region image after positioning and cropping processing,and the spatial and temporal features are obtained by combining the VGG network and the deep Bi-LSTM network to realize the accurate identification of the cigarette code.Experimental result has an accuracy rate of 91.9%in detection,83.4%in recognition,the testing accuracy after deploying the mobile APP is 83.0%,which shows that the method proposed in this paper can provide accurate cigarette laser code recognition effect.

关 键 词：卷烟激光码 目标检测 文本识别 DBNet CRNN 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]