Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm
To improve the performance of Radio Frequency Identification (RFID) multi-label systems, the multi-label network structure needs to be quickly located and optimized. A multi-label location measurement method based on the NLM–Harris algorithm is proposed in this paper. Firstly, multi-label geometric...
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2025-01-01
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| Online Access: | https://www.mdpi.com/1424-8220/25/2/426 |
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| author | Lin Li Zhixin Jin Junji Li Zelin Zhang |
| author_facet | Lin Li Zhixin Jin Junji Li Zelin Zhang |
| author_sort | Lin Li |
| collection | DOAJ |
| description | To improve the performance of Radio Frequency Identification (RFID) multi-label systems, the multi-label network structure needs to be quickly located and optimized. A multi-label location measurement method based on the NLM–Harris algorithm is proposed in this paper. Firstly, multi-label geometric distribution images are obtained through a label image acquisition system of a multi-label semi-physical simulation platform with two vertical Charge-Coupled Device (CCD) cameras, and Gaussian noise is added to the image to simulate thermoelectric interference. Then, a fast NLM algorithm that optimizes the kernel coefficient acquisition speed is used for image denoising. Finally, the Harris corner algorithm is used to obtain the corner points of the images. After screening the diagonal points, the pixel coordinates of the preset origin and the four corners of the labels are obtained. Furthermore, the actual coordinates of the labels are obtained according to the pixel relationship. The results show that the average absolute errors of x, y, and z coordinates are 0.773 mm, 0.782 mm, and 0.807 mm, respectively. In addition, the relative errors are 1.659%, 2.260%, and 0.258%, which shows the high location accuracy of the multi-label network. It is of great significance to measure and optimize the performance of multi-label systems. |
| format | Article |
| id | doaj-art-83abdff3cf8d4639af788b701616eb68 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-83abdff3cf8d4639af788b701616eb682025-01-24T13:48:53ZengMDPI AGSensors1424-82202025-01-0125242610.3390/s25020426Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris AlgorithmLin Li0Zhixin Jin1Junji Li2Zelin Zhang3School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, ChinaCollege of Physical Education, Taiyuan University of Science and Technology, Taiyuan 030024, ChinaSchool of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, ChinaPeking University Yangtze River Delta Institute of Optoelectronics, Nantong 100871, ChinaTo improve the performance of Radio Frequency Identification (RFID) multi-label systems, the multi-label network structure needs to be quickly located and optimized. A multi-label location measurement method based on the NLM–Harris algorithm is proposed in this paper. Firstly, multi-label geometric distribution images are obtained through a label image acquisition system of a multi-label semi-physical simulation platform with two vertical Charge-Coupled Device (CCD) cameras, and Gaussian noise is added to the image to simulate thermoelectric interference. Then, a fast NLM algorithm that optimizes the kernel coefficient acquisition speed is used for image denoising. Finally, the Harris corner algorithm is used to obtain the corner points of the images. After screening the diagonal points, the pixel coordinates of the preset origin and the four corners of the labels are obtained. Furthermore, the actual coordinates of the labels are obtained according to the pixel relationship. The results show that the average absolute errors of x, y, and z coordinates are 0.773 mm, 0.782 mm, and 0.807 mm, respectively. In addition, the relative errors are 1.659%, 2.260%, and 0.258%, which shows the high location accuracy of the multi-label network. It is of great significance to measure and optimize the performance of multi-label systems.https://www.mdpi.com/1424-8220/25/2/426measurementCCDRFIDimage processinggolden sectionHarris corner detection |
| spellingShingle | Lin Li Zhixin Jin Junji Li Zelin Zhang Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm Sensors measurement CCD RFID image processing golden section Harris corner detection |
| title | Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm |
| title_full | Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm |
| title_fullStr | Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm |
| title_full_unstemmed | Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm |
| title_short | Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm |
| title_sort | novel rfid multi label network location measurement by dual ccd and non local means harris algorithm |
| topic | measurement CCD RFID image processing golden section Harris corner detection |
| url | https://www.mdpi.com/1424-8220/25/2/426 |
| work_keys_str_mv | AT linli novelrfidmultilabelnetworklocationmeasurementbydualccdandnonlocalmeansharrisalgorithm AT zhixinjin novelrfidmultilabelnetworklocationmeasurementbydualccdandnonlocalmeansharrisalgorithm AT junjili novelrfidmultilabelnetworklocationmeasurementbydualccdandnonlocalmeansharrisalgorithm AT zelinzhang novelrfidmultilabelnetworklocationmeasurementbydualccdandnonlocalmeansharrisalgorithm |