- Full text PDF available (15)
- This year (0)
- Last 5 years (0)
- Last 10 years (0)
Journals and Conferences
We develop an O(n2) time serial algorithm to obtain the medial axis transform (MAT) of an n×n image. An O(logn) PRAM and an O(log2n) hypercube parallel algorithm for the MAT are also developed. Both of these use O(n2) processors. Two problems associated with the MAT are also studied. These are the area and perimeter reporting problem. We develop an O(logn)… (More)
Computing the configuration space obstacles is an important problem in spatial planning for robotics applications. In this paper, we present parallel algorithm for computing the configuration space obstacles by using hypercube multiprocessors. The digitized images of the obstacles and the robot are stored in an N x N image plane. An algorithm for handling… (More)
Parallel reconfigurable mesh algorithms are developed for the following image processing problems: shrinking, expanding, clustering, and template matching. Our N×N reconfigurable mesh algorithm for the q-step shrinking and expansion of a binary image takes O (1) time. One pass of the clustering algorithm for N patterns and K centers can be done in O (MK +… (More)
Two plausible ways to implement Floyd’s all pairs shortest paths algorithm on a hypercube mutiprocessor are considered. These are evaluated experimentally. A comparison with using Dijkstra’s single source all desitination algorithm on each processor is also done.
We develop reconfigurable mesh (RMESH) algorithms for window broadcasting, data shifts, and consecutive sum. These are then used to develop efficient algorithms to compute the histogram of an image and to perform histogram modification. The histogram of an N×N image is computed by an N×N RMESH in O (√ B log√ B (N/√ B ) for B < N, Ο(√ N ) for B = N, and Ο(√… (More)
We develop two algorithms to perform the q step shrinking and expanding of an N×N binary image on a pyramid computer with an N×N base. The time complexity of both algorithms is O(√ q ). However, one uses O(√ q ) space per processor while the per processor space requirement of the other is O (1).
Parallel reconfigurable mesh computer algorithms are developed to obtain the area and perimeter of image components. For an N×N image, our algorithms take O (logN) time on an N×N RMESH.
Recently, several similar reconfigurable mesh (RMESH) architectures have been proposed [MILL88abc, LI89ab, BEN90]. It has been demonstrated that these architectures are often very easy to program and that in many cases it is possible to obtain constant time algorithms that use a polynomial number of processors for problems that are not so solvable using the… (More)