An improved Hough transform technique based on error propagation

This paper describes a Bayesian scheme for incrementing the Hough Transform (NT) accumulator to improve the performance of the HT, making it more robust to noise. The proposed technique analytically computes the uncertainty of each feature point based on its gradient and location in the image. Using the estimated uncertainty of each feature point, a Bayesian probabilistic scheme is proposed to compute the contribution of each feature point to the accumulator. A performance evaluation of our technique reveals its superior performance, especially for noisy images.