FPGA implementation of ellipse fitting based on least squares

Hao Yang; Quanqin Gao; Haiyang Sun; Qingyu Cai; Xiaoan Tang

doi:10.1117/12.3011546

7 December 2023 FPGA implementation of ellipse fitting based on least squares

Hao Yang, Quanqin Gao, Haiyang Sun, Qingyu Cai, Xiaoan Tang

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129411R (2023) https://doi.org/10.1117/12.3011546
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Ellipse fitting is widely used in image processing, machine vision and other fields. Aiming at the problems of large data computation, high complexity and longtime consumption in the implementation of ellipse fitting algorithm by programmable gate array (FPGA), this paper proposes an FPGA implementation method of ellipse fitting based on least squares. This method is based on the principle of least squares. In the ellipse fitting problem under constraints, the generalized eigenvalue and eigenvector problem of the sixth-order matrix is avoided, and it is transformed into the eigenvalue and eigenvector of the general third-order matrix. Householder transformation and Givens rotation are used to greatly reduce the computational complexity. The simulation results show that the method still has high accuracy when using fixed-point number calculation.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hao Yang, Quanqin Gao, Haiyang Sun, Qingyu Cai, and Xiaoan Tang "FPGA implementation of ellipse fitting based on least squares", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129411R (7 December 2023); https://doi.org/10.1117/12.3011546

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