A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Detecting partially occluded ellipses using the Hough transform
Image and Vision Computing - 4th Alvey Vision Meeting
A probabilistic Hough transform
Pattern Recognition
Ellipse detection and matching with uncertainty
Image and Vision Computing - Special issue: BMVC 1991
A note on the least squares fitting of ellipses
Pattern Recognition Letters
Ellipse fitting by accumulating five-point fits
Pattern Recognition Letters
Unbiased Estimation of Ellipses by Bootstrapping
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
Randomized or probabilistic Hough transform: unified performance evaluation
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Hypothesis Testing: A Framework for Analyzing and Optimizing Hough Transform Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonparametric Segmentation of Curves into Various Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Technique for Ellipse Detection Using Restricted Randomized Hough Transform
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
The Distinctiveness of a Curve in a Parameterized Neighborhood: Extraction and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Localization with Dual Coarse-to-fine Strategy
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Arc-based evaluation and detection of ellipses
Pattern Recognition
Part-Based Object Retrieval in Cluttered Environment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segment Hough Transform -- a Novel Hough-based Algorithm for Curve Detection
ICIG '07 Proceedings of the Fourth International Conference on Image and Graphics
A hierarchical approach for fast and robust ellipse extraction
Pattern Recognition
Comparison and improvement of tangent estimators on digital curves
Pattern Recognition
Multiple ellipses detection in noisy environments: A hierarchical approach
Pattern Recognition
Splitting touching cells based on concave points and ellipse fitting
Pattern Recognition
Structural descriptors for category level object detection
IEEE Transactions on Multimedia
Error Analysis of Geometric Ellipse Detection Methods Due to Quantization
PSIVT '10 Proceedings of the 2010 Fourth Pacific-Rim Symposium on Image and Video Technology
An error bounded tangent estimator for digitized elliptic curves
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
A novel iris segmentation method for hand-held capture device
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A Split and Merge Based Ellipse Detector With Self-Correcting Capability
IEEE Transactions on Image Processing
New hypothesis distinctiveness measure for better ellipse extraction
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
A precise ellipse fitting method for noisy data
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
A novel framework for making dominant point detection methods non-parametric
Image and Vision Computing
EDCircles: A real-time circle detector with a false detection control
Pattern Recognition
Geometric property based ellipse detection method
Journal of Visual Communication and Image Representation
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In this paper, we propose a novel ellipse detection method for real images. The proposed method uses the information of edge curvature and their convexity in relation to other edge contours as clues for identifying edge contours that can be grouped together. A search region is computed for every edge contour that contains other edge contours eligible for grouping with the current edge contour. A two-dimensional Hough transform is performed in an intermediate step, in which we use a new 'relationship score' for ranking the edge contours in a group, instead of the conventional histogram count. The score is found to be more selective and thus more efficient. In addition, we use three novel saliency criteria, that are non-heuristic and consider various aspects for quantifying the goodness of the detected elliptic hypotheses and finally selecting good elliptic hypotheses. The thresholds for selection of elliptic hypotheses are determined by the detected hypotheses themselves, such that the selection is free from human intervention. The method requires a few seconds in most cases. So, it is suitable for practical applications. The performance of the proposed ellipse detection method has been tested on a dataset containing 1200 synthetic images and the Caltech 256 dataset containing real images. In both cases, the results show that the proposed ellipse detection method performs far better than existing methods and is close to the ideal results, with precision, recall, and F-measure, all very close to 1. Further, the method is robust to the increase in the complexity of the images (such as overlapping ellipses, occluded ellipses), while the performance of the contemporary methods deteriorates significantly.