An improved constant-time algorithm for computing the Radon and Hough transforms on a reconfigurable mesh

The Hough transform is an important problem in image processing and computer vision. Recently, an efficient algorithm for computing the Hough transform has been proposed on a reconfigurable array [12]. For a problem with an √N x √N image and an n x n parameter space, the algorithm runs in a constant time on a three-dimensional (3-D) n x n x N reconfigurable mesh where the data bus is N^1/c-bit wide. To our best knowledge, this is the most efficient constant-time algorithm for computing the Hough transform on a reconfigurable mesh. In this paper, an improved Hough transform algorithm on a reconfigurable mesh is proposed. For the same problem, our algorithm runs in constant time on a 3-D n * n x √N x √N reconfigurable mesh, where the data bus is only log N-bit wide. In most practical situations, n = O(√N). Hence, our algorithm requires much less VLSI area to accomplish the same task. In addition, our algorithm can compute the Radon transform (a generalized Hough transform) in O(1) time on the same model, whereas the algorithm in [12].