A Neighbor-finding Algorithm for Bincode-based Images on Reconfigurable Meshes.

Article · January 2000with2 Reads
DOI: 10.1093/comjnl/43.4.315 · Source: DBLP

Using bincodes to represent binary images is a storage-saving encoding scheme. Finding neighbors is one of the most important operations in spatial data structures. This paper presents an efficient parallel algorithm for solving the problem of neighbor-finding for a bincode-based binary image. Given a set of the bincodes of n blocks, the neighbor-finding algorithm can be accomplished in O(1)-time on an n 1/2 ×n 1/2 ×n 1/2 reconfigurable mesh. Under the same time bound, i.e. constant time, the number of processors used in the proposed parallel algorithm is O(n 3/2 ) and is less than that of the previous fastest one on a mesh with multiple broadcasting buses which needs O(n 2 ) processors.

  • [Show abstract] [Hide abstract] ABSTRACT: The reconfigurable mesh (RMESH) is an array of mesh-connected processors equipped with a reconfigurable bus system, which can dynamically connect the processors in various patterns. A 2D reconfigurable mesh can be used to solve motion planning problems in robotics research, in which the 2D image of robot and obstacles are digitized and represented one pixel per processor. In this paper, we present an algorithm to compute a collision-free path between two points in an environment containing obstacles. The time complexity of the algorithm is O(k) for each pair of source/destination points, with O(log2N) preprocessing time, where k is the number of obstacles in the working environment, and N is the size of the reconfigurable mesh.
    No preview · Article · Sep 2008 · Parallel Computing
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