Numpy Implementation of Hyperaccurate Ellipse fitting

• Hyperaccurate Ellipse Fitting without Iterations(Kanatani et al; 2010)
• Hyper-renormalization: Non-minimization Approach for Geometric Estimation (Kanatani et al; 2014)

Basic Usage

>>> import hyperaccurate_ellipse_fitting as hef
>>> hef.available_methods()[0]
{'name': 'hyper', 'description': ...}
>>> data = ...  # N x 2 array
>>> hef.fit(data, f0=np.linalg.norm(data, axis=1).mean(), n_max_iter=100)
...

By default function fit returns "Algebraic Representation" of ellipse, which is the coefficients of defining polynomial. The other useful representation is "Affine Representation"; tilt, center, axes length of the ellipse. To convert between those parameter representations, use affine2algebraic or algebraic2affine.

Reproduction

From paper:

Reproduced by python -m hyperaccurate_ellipse_fitting.benchmark:

Test

pytest hyperaccurate_ellipse_fitting/elltools.py --doctest-modules