The Hough Transform is a feature extraction technique for computer vision and image processing. It was invented in 1959 to detect lines in bubble chamber photographs. It was patented in 1962 and popularized by Duda and Hart in 1972 [1]. This tutorial uses the line detection style of Hough Transform only.
The Hough Transform detects lines using a parametric representation. It transforms lines from normal \((x,y)\) coordinates into a \((\rho,\theta)\) domain. Here, \(\rho\) represents the perpendicular distance from the origin, and \(\theta\) identifies the angle to the x-axis. The following diagram shows this transformation. Notice all points on the red line have the same \((\rho,\theta)\) values. When every pixel associates with a \((\rho,\theta)\) pair, you can identify lines through histogram analysis. These histogram statistics in the \((\rho,\theta)\) plane identify lines in the original image.