On the Sensitivity of the Hough Transform for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method to Detect and Characterize Ellipses Using the Hough Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Further five-point fit ellipse fitting
Graphical Models and Image Processing
Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Nonparametric Segmentation of Curves into Various Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Least-Square Fitting of Ellipses Applied to the RobotCub Platform
SIMPAR '08 Proceedings of the 1st International Conference on Simulation, Modeling, and Programming for Autonomous Robots
Journal of Real-Time Image Processing
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This paper presents a robust and non-iterative algorithm for the least-square fitting of ellipses to scattered data. In this work, we undertake a critical analysis of a previous reported work [1] and we propose a novel approach that preserves the advantages while overcomes the major limitations and drawbacks. The modest increase of the computational burden introduced by this method is justified by the achievement of an excellent numerical stability. Furthermore the method is simple and accurate and can be implemented with fixed time of computation. These characteristics coupled to its robustness and specificity makes the algorithm well-suited for applications requiring real-time machine vision.