A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Randomized Hough transform: improved ellipse detection with comparison
Pattern Recognition Letters
Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ellipse detection based on symmetry
Pattern Recognition Letters
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
International Journal of Computer Vision - Special issue on a special section on visual surveillance
On the Fitting of Surfaces to Data with Covariances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Randomized or probabilistic Hough transform: unified performance evaluation
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Orthogonal Distance Fitting of Implicit Curves and Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
From FNS to HEIV: A Link between Two Vision Parameter Estimation Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Arc-based evaluation and detection of ellipses
Pattern Recognition
A hierarchical approach for fast and robust ellipse extraction
Pattern Recognition
Multiple ellipses detection in noisy environments: A hierarchical approach
Pattern Recognition
Feature vector field and feature matching
Pattern Recognition
Quantization-free parameter space reduction in ellipse detection
Expert Systems with Applications: An International Journal
Robust ellipse and spheroid fitting
Pattern Recognition Letters
Edge curvature and convexity based ellipse detection method
Pattern Recognition
A Split and Merge Based Ellipse Detector With Self-Correcting Capability
IEEE Transactions on Image Processing
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In this paper a simple but effective and robust ellipse detection method based on geometric property is developed, which mainly utilizes the following two aspects of ellipse geometric information: (1) Points on ellipse contour are position-symmetric and the gradient vectors of one pair of symmetric points are parallel or anti-parallel, the fact of which can be used for ellipse center location. In this part, the inner product in mathematics is introduced to evaluate the extent of parallelism of two gradient vectors, and then two concepts, inner product symmetrical energy (IPSE) and inner product consistent energy (IPCE), is defined to compute the probability of a position as a symmetric center. (2) The sum of distances of one contour point far from ellipse's two foci is a constant. For two given positions, by computing the distribution of the sum of distances we can validate if they are the correct positions of ellipse foci. Furthermore, ellipse's semi-major axis can be also estimated from distance distribution on the positions of ellipse foci. After determining the center, foci and semi-major axis of an ellipse candidate, other parameters can be easily deduced by resolving the elliptic equation directly. Compared with existing methods, the proposed method detects the ellipse using the geometric properties directly while avoiding the complicated application of the ellipse parameter space or fitting step, and it is simple, effective and robust. In addition, the ideas proposed in this paper can be extended for other features extraction, such as general symmetry center location and other shapes detection, and extensive experiments show the good availability of the proposed ideas.