Trends in astronomical image processing
Computer Vision, Graphics, and Image Processing
Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symmetry as a Continuous Feature
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rectilinearity Measurements for Polygons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Measuring shape: ellipticity, rectangularity, and triangularity
Machine Vision and Applications
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Notes on shape orientation where the standard method does not work
Pattern Recognition
Pattern Recognition
Measuring Elongation from Shape Boundary
Journal of Mathematical Imaging and Vision
Measuring linearity of planar point sets
Pattern Recognition
A Hu moment invariant as a shape circularity measure
Pattern Recognition
Shape ellipticity based on the first Hu moment invariant
Information Processing Letters
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A new ellipticity measure is proposed in this paper. The acquired shape descriptor shows how much the shape considered differs from a perfect ellipse. It is invariant to scale, translation, rotation and it is robust to noise and distortions. The new ellipticity measure ranges over (0, 1] and gives 1 if and only if the measured shape is an ellipse. The proposed measure is theoretically well founded, implying that the behaviour of the new measure can be well understand and predicted to some extent, what is always an advantage when select the set of descriptors for a certain application. Several experiments are provided to illustrate the behaviour and performance of the new measure.