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Analysis of Grid Computing as It Applies to High-Volume Document Processing and Optical Character Recognition

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Summary

In this paper we analyze the concept of grid programming as it applies to document imaging and processing. The paper mostly focuses on optical character recognition (OCR) processing mapped to a simple grid configuration. Alchemi .NET grid framework was used as the grid engine. Basic dependences of the OCR engine behavior in the grid configuration are discussed and the increase of the document processing rate is demonstrated. Based solely on the small sample and test regimen employed, we demonstrate that throughput in excess of 150 percent can be achieved even in this CPU intensive process by employing grid strategies.

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About The Author

Stephen Pearson has more than fifteen years of imaging experience including FileNet, Eastman, Open Text and IBM. Currently he works as freelance consultant.

Dmitri Ilkaev has more than twenty years of experience in software and technology development. He holds Ph.D. in Computer Sciences from Moscow Institute of Physics and Technology. He can be reached at [email protected].

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