A robust Hough transform based on validity

We propose a robust Hough transform (RHT) which addresses many of the problems associated with the conventional Hough transform (HT). The bin-splitting problem is solved by the use of robust clustering for peak detection, the accuracy problem is solved by means of an analog Hough space, the bias problem is solved by the multiple-point method combined with random sampling, and the spurious peak problem is solved by the use of a validity measure. We present experimental results of the proposed RHT on real images.