Pyramid simulation of image processing applications

Detecting lines in images using pyramid architecture is the main subject of this paper. The approach is based on the parallel calculation of Hough Transform. A pyramid architecture of size n is a ne-grain architecture with a mesh base of size p n p n processors each holding a single pixel of the image. The pyramid operates in an SIMD mode. Two algorithms for computing the Hough Transform are explained. The rst algorithm initially uses diierent angles, j 's, and its complexity is O(k+log 2 n) with O(m) storage requirement. The second algorithm computes the Hough Transform in a pipeline fashion for each angle j at a time. This method produces results in O(k log 2 n) time with O(1) storage, where k is the number of j angles, m is the number of i normal distances from the origin, and n is the number of pixels. A simulation program is also described.