Vision algorithms for hypercube machines |
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Affiliation: | 1. The Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China;2. Stony Brook University, Stony Brook, NY 11794-2424, United States;1. School of Biological Sciences, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia;2. Centre for Chemical Biology, Universiti Sains Malaysia, 11900 Bayan Lepas, Penang, Malaysia |
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Abstract: | Several commercial hypercube parallel processors with the potential to deliver massive parallelism cost-effectively have been announced recently. They open the door to a wide variety of application areas that could benefit from parallelism. Computer vision is one of these application areas. This paper develops a general model for hypercube machines, and uses it to show how vision algorithms can be executed on hypercubes. In particular, the steps in the problem of thick-film inspection are used as a concrete example. The time needed to complete a typical inspection is used to demonstrate the performance of hypercube machines. Experimental results from a hypercube machine illustrate the potential use of such machines. |
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