The Hough transform has many applications in image processing and computer vision, including line detection, shape recognition and range alignment for moving imaging objects. Many constant-time algorithms for computing the Hough transform have been proposed on reconfigurable meshes [1, 5, 6, 7, 9, 10]. Among them, the ones described in [1, 10] are the most efficient. For a problem with an N × N image and an n × n parameter space, the algorithm in [1] runs in a constant time on a 3D nN × N × N reconfigurable mesh, and the algorithm in [10] runs in a constant time on a 3D n2 × N × N reconfigurable mesh. In this paper, a more efficient Hough transform algorithm on a 3D reconfigurable mesh is proposed. For the same problem, our algorithm runs in constant time on a 3D n log2 N × N × N reconfigurable mesh. © 2000 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Pan, Y. (2000). Constant-time Hough transform on a 3D reconfigurable mesh using fewer processors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1800 LNCS, pp. 966–973). Springer Verlag. https://doi.org/10.1007/3-540-45591-4_132
Mendeley helps you to discover research relevant for your work.