Distance and Angles Effect in Hough Transform for line detection

In this paper, we study the Hough transform theory images by generating the peak point from gray scale images, and seek for the effect caused by the distance and the angles. Lines will appear on the edge of images, which has been processed edge detection theorem. The input to a Hough transform is normally an image that has been edge detected with a Robert, Sobel or Canny edge detector, for instance. Problems occur in lines detection due to several reasons. They are noise, low resolution and un-sharp object boundaries. The Hough Transform is a standard tool in image analysis that detects lines in an image, by grouping isolated collinear or almost collinear points into image structures. To simplify the computation, the paprameter can be divbided into distance and angles paprameters where both parameter to achieve the enhancment of straight line detection using Hough Transform. Hough Transform can be regarded as an edge linker since it groups edge pixels together and describes by a higher order entity such as a line equation. However the Hough transform can be used to extract circles and even generalised (perhaps nonsymmetrical) shapes. In this case it is more like a pattern matcher. Even though that the Hough transform is invariant to rotation and translation. Key word: (Auto lines, Hough transform) Detection