Hypercube algorithms: with applications to image processing and pattern recognition
Hypercube algorithms: with applications to image processing and pattern recognition
Pipelined communications in optically interconnected arrays
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
IEEE Transactions on Parallel and Distributed Systems
Linear array with a reconfigurable pipelined bus system—concepts and applications
Information Sciences: an International Journal - special issue on parallel and distributed processing
Journal of the ACM (JACM)
Computing Moments by Prefix Sums
Journal of VLSI Signal Processing Systems
New bounds for parallel prefix circuits
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Efficient hardware architectures for computation of image moments
Real-Time Imaging
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Efficient computation of local geometric moments
IEEE Transactions on Image Processing
High-order moment computation of gray-level images
IEEE Transactions on Image Processing
Fast and scalable selection algorithms with applications to median filtering
IEEE Transactions on Parallel and Distributed Systems
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Image moments are used in image analysis for object modelling and matching. The moment computation of a two-dimensional (2D) image involves a significant amount of multiplication and addition in a direct method. In this paper, we use the suffix sum functions to compute the gray-level image moments instead of using a direct method. This new method can reduce drastically the number of multiplications required. We first derive the mathematical relationships between moment computations and suffix sums. Based on the derived mathematical relationships, four new parallel algorithms for computing image moments are derived on various computational models. By integrating the advantages of both optical transmission and electronic computation, the 2D image moments can be computed in constant time on a 2D array with reconfigurable optical buses. The performance comparison shows that the proposed method is fast and efficient. In addition, three scalable and cost optimal algorithms are derived on the AROB, the hypercube computer and the EREW PRAM model.