Abstract
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 n 2 × 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 log2N × N × N reconfigurable mesh.
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Pan, Y. (2000). Constan t-Time Hough Transform On A 3D Reconfigurable Mesh Using Fewer Processors. In: Rolim, J. (eds) Parallel and Distributed Processing. IPDPS 2000. Lecture Notes in Computer Science, vol 1800. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45591-4_132
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DOI: https://doi.org/10.1007/3-540-45591-4_132
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