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Improving Image Processing Systems by Artificial Neural Networks

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Reading and Learning

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2956))

Abstract

Document analysis systems require documents in electronic format. An image acquisition and display system for scanning and saving documents is presented, whereby the recognition capability (for example, series-connected OCR systems) is improved by correction components. Components for improving image acquisition, archiving documents and for reducing compression errors during archiving are integrated in the overall solution. The deployed components are suitably trained artificial neural networks. The projected improvements are assessed.

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Rebmann, R., Michaelis, B., Krell, G., Seiffert, U., PĆ¼schel, F. (2004). Improving Image Processing Systems by Artificial Neural Networks. In: Dengel, A., Junker, M., Weisbecker, A. (eds) Reading and Learning. Lecture Notes in Computer Science, vol 2956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24642-8_4

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  • DOI: https://doi.org/10.1007/978-3-540-24642-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21904-0

  • Online ISBN: 978-3-540-24642-8

  • eBook Packages: Springer Book Archive

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