A novel method for 3D measurement of RFID multi-tag network using a machine vision system

• Autorzy: Zhuang X. , Yu X. , Zhao Z. , Zhang W. , Liu Z. , Lu D. , Dong D.

Identyfikatory

DOI

10.24425/123898

• Języki publikacji: EN

Abstrakty

EN

The three-dimensional (3D) coordinate measurement of radio frequency identification (RFID) multi-tag networks is one of the important issues in the field of RFID, which affects the reading performance of RFID multi-tag networks. In this paper, a novel method for 3D coordinate measurement of RFID multi-tag networks is proposed. A dual-CCD system (vertical and horizontal cameras) is used to obtain images of RFID multi-tag networks from different angles. The iterative threshold segmentation and the morphological filtering method are used to process the images. The template matching method is respectively used to determine the two-dimensional (2D) coordinate and the vertical coordinate of each tag. After that, the 3D coordinate of each tag is obtained. Finally, a back-propagation (BP) neural network is used to model the nonlinear relationship between the RFID multi-tag network and the corresponding reading distance. The BP neural network can predict the reading distances of unknown tag groups and find out the optimal distribution structure of the tag groups corresponding to the maximum reading distance. In the future work, the corresponding in-depth research on the neural network to adjust the distribution of tags will be done.

Słowa kluczowe

EN

3D measurement; RFID multi-tag network; dual-CCD system; neural network; machine vision

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2018
• Tom: Vol. 25, nr 3
• Strony: 475--486
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Zhuang X.

• Nanjing University of Aeronautics and Astronautics, College of Science, Nanjing 210016, People’s Republic of China
• National Quality Supervision and Testing Center for RFID Product, Jiangsu, Nanjing 210029, People’s Republic of China

autor

Yu X.

• Nanjing University of Aeronautics and Astronautics, College of Science, Nanjing 210016, People’s Republic of China
• National Quality Supervision and Testing Center for RFID Product, Jiangsu, Nanjing 210029, People’s Republic of China

autor

Zhao Z.

• Nanjing University of Aeronautics and Astronautics, College of Science, Nanjing 210016, People’s Republic of China

autor

Zhang W.

• Nanjing University of Aeronautics and Astronautics, College of Science, Nanjing 210016, People’s Republic of China

autor

Liu Z.

• Nanjing University of Aeronautics and Astronautics, College of Science, Nanjing 210016, People’s Republic of China

autor

Lu D.

• Nanjing University of Aeronautics and Astronautics, College of Science, Nanjing 210016, People’s Republic of China

autor

Dong D.

• Nanjing University of Aeronautics and Astronautics, College of Science, Nanjing 210016, People’s Republic of China

Bibliografia

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• [3] Kang, M.S., Lee, C.H., You, B.M., Chung, Y.S. (2015). A 3D object measurement method using a single view camera. IEEE, Information and Communication Technology Convergence, Jeju, South Korea, 790-792.
• [4] Kavitha, C., Ashok, S.D. (2017). A new approach to spindle radial error evaluation using a machine vision system. Metrol. Meas. Syst., 24(1), 201-219.
• [5] Pu, L., Tian, R., Wu, H.C., Yan, K. (2016). Novel object-size measurement using the digital camera. IEEE, Advanced Information Management, Communicates, Electronic and Automation Control Conference. Xi’an, China, 543-548.
• [6] Feng, S., Chen, Q., Zuo, C., Sun, J., Yu, S.L. (2014). High-speed real-time 3-D coordinates measurement based on fringe projection profilometry considering camera lens distortion. Optics Communications, 329, 44-56.
• [7] Chen, F., Chen, X., Xie, X., Feng, X., Yang, L. (2013). Full-field 3D measurement using multi-camera digital image correlation system. Optics and Lasers in Engineering, 51(9), 1044-1052.
• [8] You, S.J., Truong, P.H., Ji, S.H., Lee, S.M., Lee, C.E., Cho, Y.J. (2014). A cooperative multi-camera system for tracking a fast moving object. IEEE, Cyber Technology in Automation, Control, and Intelligent Systems . Hong Kong, China, 141-145.
• [9] Valero, E., Adán, A., Cerrada, C. (2015). Evolution of RFID applications in construction: a literature review. Sensors, 15(7), 15988-16008.
• [10] Li, Z., He, C., Li, J., Huang, X. (2014). RFID reader anti-collision algorithm using adaptive hierarchical artificial immune system. Expert Systems with Applications, 41(5), 2126-2133.
• [11] Joo, Y.I., Seo, D.H., Kim, J.W. (2014). An efficient anti-collision protocol for fast identification of RFID tags. Wireless personal communications, 77(1), 767-775.
• [12] Myung, J., Lee, W., Srivastava, J. (2006). Adaptive binary splitting for efficient RFID tag anti-collision. IEEE communications letters, 10(3), 144-146.
• [13] Ni, L.M., Liu, Y., Lau, Y.C., Patil, A.P. (2004). LANDMARC: Indoor location sensing using active RFID. Wireless networks, 10(6), 701-710.
• [14] Zhao, Y., Ni, L.M. (2013). VIRE: Virtual reference elimination for active RFID-based localization. Adhoc & Sensor Wireless Networks, 17, 169-191.
• [15] Scherhäufl, M., Pichler, M., Stelzer, A. (2015). UHF RFID localization based on phase evaluation of passive tag arrays. IEEE Transactions on Instrumentation and Measurement, 64(4), 913-922.
• [16] Yu, Y., Yu, X., Zhao, Z., Liu, J., Wang, D. (2016). Measurement uncertainty limit analysis of biased estimators in RFID multiple tags system. IET Science, Measurement & Technology, 10(5), 449-455.

Uwagi

EN

1. The work has been financially supported by the National Natural Science Foundation of China under Grant No. 61771240; China Postdoctoral Science Foundation under Grant No. 2015M580422 & No. 2016T90452; Jiangsu Province Natural Science Foundation for Youths under Grant No. BK20141032; Science and Technology Project of AQSIQ under Grant 2017QK117 & 2013QK194, as well as the 352 Talent Project of Jiangsu Bureau of Quality and Technical Supervision.

PL

2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).