A novel and uniform image partitioning on spiral architecture
International Journal of Computational Science and Engineering
Complete image partitioning on spiral architecture
ISPA'03 Proceedings of the 2003 international conference on Parallel and distributed processing and applications
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Image matching based on image feature pixels involves heavily iterated computation and frequent memory access. The key to increase the speed is to employ parallelism on either parallel machines or workstation clusters. This paper presents the development of a parallel image matching system which uses a divide-and-conquer method to implement the proposed hierarchical matching scheme on a networked workstation cluster. Our investigation shows that a distributed workstation cluster can best meet the demand of high computation and memory access in image processing. The performance of our proposed matching scheme is evaluated in terms of execution time.