Hough Transform

Probabilistic Hough Transform

Background The standard Hough Transform (SHT) is used to determine the parameters of features such as lines and curves within an image. A binary image is used as input where each active pixel represents part of an edge feature. The SHT maps each of these pixels to many points in Hough (or parameter) space. In the case of line detection, a single edge pixel is mapped to a sinusoid in 2D paramete...

Randomized Hough Transform

Proposed in 1962, the Hough transform (HT) has been widely applied and investigated for detecting curves, shapes, and motions in the fields of image processing and computer vision. However, the HT has several shortcomings, including high computational cost, low detection accuracy, vulnerability to noise, and possibility of missing objects. Many efforts target at solving some of the problems for...

Advanced Hough Transform Implementations

Fast linear Hough transform

The Hough Transform is the choice technique for identifying straight lines through digital images, with applications to high energy physics and computer vision. Classical methods for implementing the Hough transform of a N N binary image require to compute N3 additions over n = log2(N) bits integers, hence nN3 bit operations per transform. We introduce a new algorithm for computing the fast Hou...

Fast generalized Hough transform

A fast algorithm for the generalized Hough transform (GHT) based on the use of a hierarchical processing scheme and the inverse generalized Hough operation is proposed. By reducing the size of the image portion which need be processed in the proposed fast GHT, not only the computation time but also the number of processing elements for parallel processing can be reduced. The way to apply the pr...