Robust ellipse fitting via alternating direction method of multipliers

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

14 Scopus Citations
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Author(s)

  • Junli Liang
  • Pengliang Li
  • Deyun Zhou
  • Ding Liu
  • Liansheng Sui

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)30-40
Journal / PublicationSignal Processing
Volume164
Online published29 May 2019
Publication statusPublished - Nov 2019

Abstract

The edge point errors, especially outliers, introduced in the edge detection step, will cause severe performance degradation in ellipse fitting. To address this problem, we adopt the ℓp-norm with p<2 in the direct least square fitting method to achieve outlier resistance, and develop a robust ellipse fitting approach using the alternating direction method of multipliers (ADMM). Especially, to solve the formulated nonconvex and nonlinear problem, we decouple the ellipse parameter vector in the nonlinear ℓp-norm objective function from the nonconvex quadratic constraint via introducing auxiliary variables, and estimate the ellipse parameter vector and auxiliary variables alternately via the derived numerical methods. Simulation and experimental examples are presented to demonstrate the robustness of the proposed approach.

Research Area(s)

  • Alternating direction method of multipliers (ADMM), Ellipse fitting, Ellipse parameter vector, Nonconvex optimization, Nonlinear optimization, Outlier

Citation Format(s)

Robust ellipse fitting via alternating direction method of multipliers. / Liang, Junli; Li, Pengliang; Zhou, Deyun; So, H. C.; Liu, Ding; Leung, Chi-Sing; Sui, Liansheng.

In: Signal Processing, Vol. 164, 11.2019, p. 30-40.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review