A fast RFID image matching algorithm for multi-tag identification and distribution optimization

被引：0
|
作者：
Zhang K. [1 ,2 ]
Yu X. [2 ]
Li L. [1 ,2 ]
Liu Z. [1 ,2 ]
Zhou S. [1 ,2 ]
Zhao Z. [1 ]
机构：
[1] College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing
[2] National Quality Supervision and Testing Center, RFID Product (Jiangsu), Nanjing
来源：
Journal of Algorithms and Computational Technology | 2021年 / 15卷
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Fast image matching; feature point extraction; HOG algorithm; RFID tag;
D O I：
10.1177/17483026211012617
中图分类号：
学科分类号：
摘要：
We propose an improved image matching algorithm that combines the minimum feature value algorithm to extract feature points and the direction gradient histogram to calculate the description vector. This algorithm is oriented to RFID multi-tag identification and distribution optimization in the actual scenario, and the traditional SURF algorithm has the problems of low matching accuracy and high complexity in multi-tag matching. This algorithm effectively improves the positioning accuracy of the RFID multi-tag positioning system. The experimental results show that the matching success rate of the improved algorithm in this paper is 87.4%, which is 50% higher than the SURF algorithm. Not only the matching accuracy is greatly improved, but the running speed is also increased by 48%. The algorithm in this paper has high matching accuracy and real-time performance.It provides an effective way for RFID multi-tag real-time fast matching and precise positioning. © The Author(s) 2021.
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