Algorithm for primary object recognition in the warehouse management system

2023;
: pp. 20 - 28
1
Lviv Polytechnic National University, Ukraine,Computer Engineering Department
2
Lviv Polytechnic National University

This article examines the peculiarities of warehouse management systems and presents the principles and implementation of an in-house software system for warehouse management using computer vision technology.

A structural diagram of the application is developed, which consists of eight modules: image capture service, image storage, computer vision service, database, API server, client application, task scheduler, and task queue. The architecture is designed based on cloud technologies, namely Google Cloud Platform. A computer vision algorithm for determining the state of cells in the warehouse is proposed. A functional software product based on modern technologies has been developed.

The purpose of this article is to reflect the results of the study of the subject area of warehouse management systems and to highlight the results of the implementation of a proprietary software system using computer vision.

  1. Warehouse Management System Global Market Report 2023. // The Business Research Company – 2023 - Available at: https: //www.researchandmarkets.com/ reports/5766696/warehouse-management-system-global- market-report /(Accessed: 17 September 2023).
  2. Ramaa, A., Subramanya, K. N., & Rangaswamy, T. M. Impact of warehouse management system in a supply chain, 2022. doi:10.5120/8530-2062– (International Journal of Computer Applications).
  3. Wroblewski, M.T. Advantages & Disadvantages to a Manual Inventory Control System- Available at::
  4. /(Accessed: 17 September 2023).
  5. Yan, B., Chen, Y., & Meng, X. RFID Technology Applied in Warehouse Management System, 2008. – (In 2008 ISECS International Colloquium on Computing, Communication, Control, and Management (pp. 363-367). doi:10.1109/CCCM.2008.372
  6. What is Computer Vision?.// IBM –2022 Available at: https://www.ibm.com/topics/computer-vision doi:10.3390/ai4010013  /./(Accessed: 17 September 2023)
  7. Polacco, A., & Backes, K. The Amazon Go concept: Implications, applications, and sustainability., 2018. – doi: http://doi.org/10.6347/JBM.201803_24(1).0004 (Journal of Business and Management, 24(1), 79-92).
  8. Zhao, F., Huang, Q., & Gao, W. Image matching by normalized cross-correlation., 2006. – (In 2006 IEEE international conference on acoustics speech and signal processing proceedings (Vol. 2, pp. II-II). IEEE). doi:10.1109/ICASSP.2006.1660446