Title :
Efficiently Computing Optimal Consensus of Digital Line Fitting
Author :
Kenmochi, Yukiko ; Buzer, Lilian ; Talbot, Hugues
Author_Institution :
Lab. d´´Inf. Gaspard-Monge, Univ. Paris-Est, Equipe, France
Abstract :
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.
Keywords :
computational complexity; computer vision; image denoising; digital image; digital line fitting; discrete point; linear space complexity; optimal consensus; quadratic time complexity; topological sweep; Complexity theory; Fitting; Geometry; Presses; Robustness; Strips; Transforms; digital line; fitting; optimal consensus;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.266