A High-Efficiency FPGA-Based ORB Feature Matching System

Bai Cheng Huang, Yan Jun Zhang*

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

Feature extraction and matching are the basic procedures of the so-called Visual Odometer (VO), Simultaneous Localization and Mapping (SLAM) and many other image processing algorithms. Oriented features from accelerated segment test (FAST) and rotated binary robust independent elementary features (ORB) algorithm are widely used since they are computationally faster. In this paper, we proposed a method to generate a value for a feature, the value is called signature. In the matching step, we only compute Hamming distances of descriptors with the same signatures. Hence, the matching time is shortened. Compared with the original ORB algorithm, features to be matched dropped 69.63% on TUM datasets and 85.7% on VGG datasets by adopting our strategy. In addition, the precision is above 85% on both VGG and TUM datasets. We design a customized hardware architecture for ORB feature extraction and matching based on the proposed method. The hardware structure is implemented on Xilinx ZCU102 evaluation board. The clock frequency is set to 150MHz. Our Field Programmable Gate Arrays (FPGA) system achieves 193fps on 1280 × 720 images with 1984 features on average and 314fps on 640 × 480 images with 700 features on average, which is more efficient compared to the state-of-the-art works.

源语言英语
文章编号2450028
期刊Journal of Circuits, Systems and Computers
33
2
DOI
出版状态已出版 - 30 1月 2024

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引用此

Huang, B. C., & Zhang, Y. J. (2024). A High-Efficiency FPGA-Based ORB Feature Matching System. Journal of Circuits, Systems and Computers, 33(2), 文章 2450028. https://doi.org/10.1142/S0218126624500282