An analytical least squares Hough transform

The Hough Transform (HT) is an efficient method to extract geometric features from an image which works fairly well for images that contain noise and occlusion. However, its performance decreases with image and parameter space quantisation noise. Accuracy is limited by memory costs and oversampling effects. This paper describes two HT variants based on analytical least squares refinement based on a conventional HT voting stage. Both methods reduce memory requirements. A number of experimental results are presented and compared with the standard HT