Probabilistic and non-probabilistic Hough transforms: Overview and comparisons

http://www.biblioteca.uma.es/bbldoc/tesisuma/16603667.pdf

Mean shift based clustering of Hough domain for fast line segment detection

Real-Time Detection of Lines and Grids

An extended Hough Transform is proposed to estimate the velocity of Regions Of Interest (ROI). Each ROI is first characterized by a spatio-temporal point (centroids for example). The velocity of each point is then computed by searching the line that passes through this point and fits at best the other ones. In order to avoid high dimension problems (a three-dimensional (3D) spatio-temporal line is defined by four parameters), the data are projected on several planes. The velocities are deduced by combining the results obtained on each plane using weighted least squares. The robustness of this method called “Hough Transform with Projection (HTP)”, compared to the Standard Hough Transform (applied on 3D spatio-temporal data) is demonstrated. Finally, experimental results on synthetic and real sequences validate the approach.

A Hough Transform with projection for velocity estimation

Various research groups invested effort to deal with computational complexity of the Hough transform and/or to improve the accuracy of the detection. Different methods focus on special data structures, non-uniform resolution of the accumulation array, special rules for picking points from the input image, or they employ specialized hardware units, etc.

Yuval Caspi

Papers

Monte Carlo Hough Transforms