A Parallel Computing Scheme Utilizing Memristor Crossbars for Fast Corner Detection and Rotation Invariance in the ORB Algorithm

作者：Qinghui Hong, Haoyou Jiang, Pingdan Xiao, Sichun Du, Tao Li · 发表于：IEEE Transactions on Computers · 年份：2024 · DOI：10.1109/tc.2024.3504817 · 被引用次数：50 · 研究领域：Advanced Memory and Neural Computing、DNA and Biological Computing、Modular Robots and Swarm Intelligence

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$\boldsymbol{\times}$faster than traditional methods and obtains more uniform corners distribution in large-scale images.