Efficient parallel algorithms for covering binary images
Given a black and white image, represented by an array of {radical}n x {radical}n binary valued pixels, the author wishes to cover the black pixels with a minimal set of (possibly overlapping) maximal squares. It was recently shown that obtaining a minimum cover with squares for a polygonal binary image having holes is NP-hard. He derives a processor-time-optimal parallel algorithm for the minimal square cover problem, which for any desired computation time T in (log n, n) runs on an EREW-PRAM with (n/T) processors. He also outlines an implementation on a mesh architecture which runs in O({radical}n) time, and is P-T-optimal. Finally, he also shows how to obtain a speedup in the running time of the algorithm when polymorphic communication primitives are available on the mesh. The cornerstone of the algorithm is a novel data structure, the cover graph, which compactly represents the covering relationships between the maximal squares of the image. The size of the cover graph is linear in the number of pixels. This algorithm has applications to problems in VLSI mask generation, incremental update of raster displays, and image compression.
- Research Organization:
- Cornell Univ., Ithaca, NY (USA)
- OSTI ID:
- 5748888
- Country of Publication:
- United States
- Language:
- English
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