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

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

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

authors

• Alnuweiri, Hussein

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

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• International Conference on Pattern Recognition  Journal

keywords

• Bioengineering

Digital Object Identifier (DOI)

• 10.1109/icpr.1990.119381

start page

• 350-355 vol.2

end page

• 355

volume

• ii

URL

• http://dx.doi.org/10.1109/icpr.1990.119381