An optimal Bayesian Hough transform for line detection

In this paper, we describe a statistically efficient Hough transform technique with improved performance in accuracy and robustness. The proposed technique analytically computes the uncertainty of each feature point based on image noise, the procedure used for estimating edge orientation, and the specific parametric representation scheme of a line. Using the estimated uncertainty of each feature point, a Bayesian probabilistic scheme is introduced to compute the contribution of each feature point to the accumulator. A performance evaluation of the technique reveals its superior performance, especially for noisy images.