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Communication Dans Un Congrès Année : 2010

Efficiently computing optimal consensus of digital line fitting

Yukiko Kenmochi
Lilian Buzer
Hugues Talbot

Résumé

Given a set of discrete points in a 2D digital image containing noise, we formulate our problem as robust digital line fitting. More precisely, we seek the maximum subset whose points are included in a digital line, called the optimal consensus. The paper presents an efficient method for exactly computing the optimal consensus by using the topological sweep, which provides us with the quadratic time complexity and the linear space complexity with respect to the number of input points.
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Dates et versions

hal-00790826 , version 1 (21-02-2013)

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Yukiko Kenmochi, Lilian Buzer, Hugues Talbot. Efficiently computing optimal consensus of digital line fitting. 20th International Conference on Pattern Recognition (ICPR), 2010, Aug 2010, Istanbul, Turkey. pp.1064-1067, ⟨10.1109/ICPR.2010.266⟩. ⟨hal-00790826⟩
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