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The Study of Print Quality Evaluation System Using the Back Propagation Neural Network with Applications to Sheet-Fed Offset

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Book cover Advances in Computer Science, Environment, Ecoinformatics, and Education (CSEE 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 214))

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Abstract

With the continuous development of the printing industry, print quality has significantly improved and enhanced. The evaluation of the print quality is mainly based on the objective and supplemented subjective methods, and it has changed from the traditional empirical judgments to science of quantitative analysis. So it improves the quality of management, scientific, standardized and rationality. This paper is to solve the color print quality problems by establishing the evaluation of index system, identifying the standard data and combining with BP neural network theory.

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References

  1. Ma, T.: Study of the Method of Evaluating Color Digital Image. In: International Conference on Computer Science and Software Engineering, ICGC 2008, pp. 225–228 (December 2008)

    Google Scholar 

  2. Otaki, N.: Colour image evaluation system. OKI Technical Review 7.0(194), 68–73 (2003)

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  3. Guan, L., Lin, J., Chen, G., Chen, M.: Study for the Offset Printing Quality Control Expert System Based on Case Reasoning. IEEE, Los Alamitos

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  4. Bohner, M., Sties, M., Bers, K.H.: An automatic measurement device for the evaluation of the print quality of printed characters. Pattern Recognition 9, 11–19 (1997)

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  5. Guan, L., Lin, J., Chen, G., Chen, M.: Study for the Offset Printing Quality Control Expert System Based on Case Reasoning. IEEE, Los Alamitos

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© 2011 Springer-Verlag Berlin Heidelberg

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Ma, T., Li, Y., Sun, Y. (2011). The Study of Print Quality Evaluation System Using the Back Propagation Neural Network with Applications to Sheet-Fed Offset. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23321-0_23

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  • DOI: https://doi.org/10.1007/978-3-642-23321-0_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23320-3

  • Online ISBN: 978-3-642-23321-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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