Efficient robust digital hyperplane fitting with bounded error
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
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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.