An Occlusion-Resistant Ellipse Detection Method by Joining Coelliptic Arcs
Autor: | Halil Ibrahim Cakir, Cuneyt Akinlar, Cihan Topal |
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Přispěvatelé: | Leibe, B, Matas, J, Sebe, N, Anadolu Üniversitesi, Topal, Cihan, Akınlar, Cüneyt |
Rok vydání: | 2016 |
Předmět: |
Hough Transform
Pixel Computer science Feature extraction Process (computing) 02 engineering and technology Ellipse 01 natural sciences Feature Extraction Hough transform law.invention Arc (geometry) Conic section law TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY Ellipse Detection 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Arc Detection 020201 artificial intelligence & image processing 010306 general physics Algorithm MathematicsofComputing_DISCRETEMATHEMATICS |
Zdroj: | Computer Vision – ECCV 2016 ISBN: 9783319464749 ECCV (2) |
ISSN: | 0003-8938 |
Popis: | 14th European Conference on Computer Vision (ECCV) -- OCT 08-16, 2016 -- -- Amsterdam, NETHERLANDS WOS: 000389383900031 In this study, we propose an ellipse detection method which gives prospering results on occlusive cases. The method starts with detection of edge segments. Then we extract elliptical arcs by computing corners and fitting ellipse to the pixels between two consecutive corners. Once the elliptical arcs are extracted, we aim to test all possible arc subsets. However, this requires exponential complexity and runtime diverges as the number of arcs increases. To accelerate the process, arc pairing strategy is deployed by using conic properties of arcs. If any pair found to be non-coelliptic, then arc combinations including that pair are eliminated. Therefore the number of possible arcs subsets is reduced and computation time is improved. In the end, ellipse fitting is applied to remaining arc combinations to decide on final ellipses. Performance of the proposed algorithm is tested on real datasets, and better results have been obtained compare to state-of-the-art algorithms. |
Databáze: | OpenAIRE |
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