A Parallel Computing Scheme Utilizing Memristor Crossbars for Fast Corner Detection and Rotation Invariance in the ORB Algorithm
The Oriented FAST and Rotated BRIEF (ORB) algorithm plays a crucial role in rapidly extracting image keypoints. However, in the domain of high-frame-rate real-time applications, the algorithm faces challenges of the speed and computational efficiency with the increase in both the size and quantity of images. To address this issue, an ORB algorithm accelerator based on a computing-in-memory (CIM) circuit is firstly proposed in this paper, which replaces the iterative calculations in traditional methods with one-step parallel analog computation. The proposed accelerator improves algorithm computational efficiency through CIM technology and enhances algorithm speed through parallel computation. Simulation demonstrate that the proposed method exhibits an average processing speed 22 <inline-formula><tex-math notation="LaTeX">$\boldsymbol{\times}$</tex-math></inline-formula> faster than traditional methods and obtains more uniform corners distribution in large-scale images.
Authors
- Huailei Jiang (ORCID: https://orcid.org/0000-0002-2170-8150)
- Sichun Du (ORCID: https://orcid.org/0000-0002-4718-8042)
- Qinghui Hong (ORCID: https://orcid.org/0000-0002-6210-6033)
- Pingdan Xiao (ORCID: https://orcid.org/0000-0002-4134-8551)
- Tao Li (ORCID: https://orcid.org/0000-0002-5728-3721)
Institutions
- Hunan University (CN)
Publication Details
- Journal
- IEEE Transactions on Computers
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1109/tc.2024.3504817
- Citations
- 41
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 8.56