Optimal image algorithms on an orthogonally-connected memory-based architecture Conference Paper uri icon

abstract

  • Processor-time optimal algorithms are presented for several image and vision problems. A parallel architecture which combines an orthogonally accessed memory with a linear array structure is used. The organization has p processors and a memory of size O(n2) locations. The number of processors p can vary over the range [1, n3/2] while providing optimal speedup for several problems in image analysis and vision. Such problems include labeling connected regions, computing minimum convex containers of regions, and computing nearest neighbors of pixels and regions. Optimal algorithms are presented for histogramming and computing the Hough transform. Such problems arise in medium-level vision and require global operations or dense data movement. It is shown that for these types of problems, the proposed organization is superior to the mesh and pyramid organizations.

name of conference

  • 10th International Conference on Pattern Recognition

published proceedings

  • [1990] Proceedings. 10th International Conference on Pattern Recognition

author list (cited authors)

  • Alnuweiri, H. M., & Kumar, V.

citation count

  • 1

complete list of authors

  • Alnuweiri, HM||Kumar, VKP

publication date

  • January 1990