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.

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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
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article

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

Huailei Jiang, Sichun Du, Qinghui Hong, Pingdan Xiao et al.
41 citations
IEEE Transactions on Computers
Advanced Memory and Neural Computing
8.56
article

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

Huailei Jiang, Sichun Du, Qinghui Hong, Pingdan Xiao, Tao Li
article en
41 citations

Abstract

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.

IEEE Transactions on ComputersVol. 74(3)
Hunan University (CN)
Affordable and clean energy
Openalex Percentile: Top 2%
Advanced Memory and Neural Computing
8.56
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A Parallel Computing Scheme Utilizing Memristor Crossbars for Fast Corner Detection and Rotation Invariance in the ORB Algorithm — Huailei Jiang, Sichun Du, et al. · IEEE Transactions on Computers (2024) | TGRS Research Map | TGRS