Design of civil aviation security check passenger identification system based on residual convolution network

IF 1.1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ning Zhang, Youcheng Liang, Loknath Sai Ambati
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引用次数: 0

Abstract

INTRODUCTION: A civil aviation security check passenger identification system based on residual convolution network is designed to improve the efficiency of airport passenger security check service. OBJECTIVES: The system uses the basic resource layer to provide communication and configuration services, collects the basic information of passengers, the images of passengers' faces and whole body, and the images of baggage security X-ray machine through the data layer, and stores the collected results in the unstructured database; METHODS: The image processing module of the business service layer calls the data in the database, and takes the STM32F103VBT6 microprocessor as the image processing control chip to complete the image data processing. The person, baggage, X-ray machine image and passenger basic information are associated through the person, baggage and X-ray machine information binding service module, and the association results are uploaded to the person and certificates integration unit of the client application layer. RESULTS: The face recognition module identifies the passenger identity through the residual convolution network with the attention mechanism, and realizes the ReID identification of passengers and baggage and the association of people and baggage through the transmission control unit. CONCLUSION: The experimental results show that the system can accurately identify the identity of civil aviation security passengers, and the identification efficiency of security passengers can reach more than 27 frames per second.
基于残差卷积网络的民航安检旅客识别系统设计
摘要:为提高机场旅客安检服务效率,设计了一种基于残差卷积网络的民航安检旅客识别系统。目的:系统利用基础资源层提供通信和配置服务,通过数据层采集旅客基本信息、旅客面部和全身图像、行李安检x光机图像,并将采集结果存储在非结构化数据库中;业务服务层的图像处理模块调用数据库中的数据,以STM32F103VBT6微处理器作为图像处理控制芯片完成图像数据处理。通过人、行李、x光机信息绑定服务模块对人、行李、x光机图像、旅客基本信息进行关联,并将关联结果上传到客户端应用层的人证集成单元。结果:人脸识别模块通过残差卷积网络结合注意机制对乘客身份进行识别,通过传输控制单元实现乘客与行李的ReID识别以及人与行李的关联。结论:实验结果表明,该系统能够准确识别民航安检旅客身份,安检旅客识别效率可达到27帧/秒以上。
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来源期刊
EAI Endorsed Transactions on Scalable Information Systems
EAI Endorsed Transactions on Scalable Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.80
自引率
15.40%
发文量
49
审稿时长
10 weeks
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