2.2 Image Feature Matching Experiment of RFID System Physical Anti-Collision
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groups of tag arrangement diagrams according to the reference image, and the tag
position was marked with a rectangular box.
According to the experimental results, SURF algorithm can effectively match the
position of key tags in the tag group. When batch identification of tag groups is
carried out, SURF algorithm is used to carry out feature matching of the collected
tag distribution images. Combined with the conclusion of the influence of key tags on
the sensitivity of tag groups obtained in this chapter, the performance of tag groups
can be evaluated and analyzed according to the results of image processing.
Combining photoelectric sensing technology and image processing technology,
tags distribution image is processed and analyzed based on the data by RFID tag
dynamic test system. From the execution time, feature point matching point number
and the correct number of SIFT algorithm, SURF algorithm and compares and
analyzes the ORB algorithm and choose SURF algorithm according to the results
of the comparison of multiple sets of tag distribution characteristic of the image
matching, the experimental results show that SURF algorithm can accomplish the
key tag positioning, so as to realize performance analysis of the RFID tag group.
This chapter is of great significance to solve the evaluation and optimization analysis of RFID multi-tag performance, at the same time, it provides an important
research foundation for upgrading the tag group sensitivity measurement system to
the performance optimization analysis system.
2.3 Conclusion
Because RFID tags have the advantages of long reading distance, high transmission efficiency, and wide range of functions, they are used in logistics, intelligent
transportation systems, and personnel positioning. As the application range of RFID
tags becomes more and more extensive, the working environment becomes more
and more complex, and the collision problem of multiple tags cannot be ignored.
Therefore, higher requirements are placed on the stability of the performance of
RFID multiple tags. This research mainly focuses on the performance evaluation of
batch identification of RFID tag groups, proposes a test and calibration method for
tag group sensitivity, and builds a dynamic test platform for tags based on photoelectric sensing. The feasibility of the proposed tag group sensitivity test and calibration
method was verified through experiments. At the same time, according to the research
results of the tag sensitivity in the tag group due to the different placement of the
tag, the performance of the tag group batch recognition was combined with image
feature matching evaluation provides a new way. This study is of great significance
to the performance evaluation of tag groups and tag groups in batch identification.
57
groups of tag arrangement diagrams according to the reference image, and the tag
position was marked with a rectangular box.
According to the experimental results, SURF algorithm can effectively match the
position of key tags in the tag group. When batch identification of tag groups is
carried out, SURF algorithm is used to carry out feature matching of the collected
tag distribution images. Combined with the conclusion of the influence of key tags on
the sensitivity of tag groups obtained in this chapter, the performance of tag groups
can be evaluated and analyzed according to the results of image processing.
Combining photoelectric sensing technology and image processing technology,
tags distribution image is processed and analyzed based on the data by RFID tag
dynamic test system. From the execution time, feature point matching point number
and the correct number of SIFT algorithm, SURF algorithm and compares and
analyzes the ORB algorithm and choose SURF algorithm according to the results
of the comparison of multiple sets of tag distribution characteristic of the image
matching, the experimental results show that SURF algorithm can accomplish the
key tag positioning, so as to realize performance analysis of the RFID tag group.
This chapter is of great significance to solve the evaluation and optimization analysis of RFID multi-tag performance, at the same time, it provides an important
research foundation for upgrading the tag group sensitivity measurement system to
the performance optimization analysis system.
2.3 Conclusion
Because RFID tags have the advantages of long reading distance, high transmission efficiency, and wide range of functions, they are used in logistics, intelligent
transportation systems, and personnel positioning. As the application range of RFID
tags becomes more and more extensive, the working environment becomes more
and more complex, and the collision problem of multiple tags cannot be ignored.
Therefore, higher requirements are placed on the stability of the performance of
RFID multiple tags. This research mainly focuses on the performance evaluation of
batch identification of RFID tag groups, proposes a test and calibration method for
tag group sensitivity, and builds a dynamic test platform for tags based on photoelectric sensing. The feasibility of the proposed tag group sensitivity test and calibration
method was verified through experiments. At the same time, according to the research
results of the tag sensitivity in the tag group due to the different placement of the
tag, the performance of the tag group batch recognition was combined with image
feature matching evaluation provides a new way. This study is of great significance
to the performance evaluation of tag groups and tag groups in batch identification.