Open Access iconOpen Access



Research on Enhanced Contraband Dataset ACXray Based on ETL

Xueping Song1,*, Jianming Yang1, Shuyu Zhang1, Jicun Zhang1,2,*

1 School of Mechanical Engineering, Dalian Jiaotong University, Dalian, 116028, China
2 Neusoft Reach Automotive Technology (Dalian) Co., Ltd., Dalian, 116085, China

* Corresponding Authors: Xueping Song. Email: email; Jicun Zhang. Email: email

(This article belongs to the Special Issue: Industrial Big Data and Artificial Intelligence-Driven Intelligent Perception, Maintenance, and Decision Optimization in Industrial Systems)

Computers, Materials & Continua 2024, 79(3), 4551-4572.


To address the shortage of public datasets for customs X-ray images of contraband and the difficulties in deploying trained models in engineering applications, a method has been proposed that employs the Extract-Transform-Load (ETL) approach to create an X-ray dataset of contraband items. Initially, X-ray scatter image data is collected and cleaned. Using Kafka message queues and the Elasticsearch (ES) distributed search engine, the data is transmitted in real-time to cloud servers. Subsequently, contraband data is annotated using a combination of neural networks and manual methods to improve annotation efficiency and implemented mean hash algorithm for quick image retrieval. The method of integrating targets with backgrounds has enhanced the X-ray contraband image data, increasing the number of positive samples. Finally, an Airport Customs X-ray dataset (ACXray) compatible with customs business scenarios has been constructed, featuring an increased number of positive contraband samples. Experimental tests using three datasets to train the Mask Region-based Convolutional Neural Network (Mask R-CNN) algorithm and tested on 400 real customs images revealed that the recognition accuracy of algorithms trained with Security Inspection X-ray (SIXray) and Occluded Prohibited Items X-ray (OPIXray) decreased by 16.3% and 15.1%, respectively, while the ACXray dataset trained algorithm’s accuracy was almost unaffected. This indicates that the ACXray dataset-trained algorithm possesses strong generalization capabilities and is more suitable for customs detection scenarios.


Cite This Article

APA Style
Song, X., Yang, J., Zhang, S., Zhang, J. (2024). Research on enhanced contraband dataset acxray based on ETL. Computers, Materials & Continua, 79(3), 4551-4572.
Vancouver Style
Song X, Yang J, Zhang S, Zhang J. Research on enhanced contraband dataset acxray based on ETL. Comput Mater Contin. 2024;79(3):4551-4572
IEEE Style
X. Song, J. Yang, S. Zhang, and J. Zhang "Research on Enhanced Contraband Dataset ACXray Based on ETL," Comput. Mater. Contin., vol. 79, no. 3, pp. 4551-4572. 2024.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 242


  • 86


  • 0


Share Link