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Historic Document Image De-noising Using Principal Component Analysis (PCA) and Local Pixel Grouping (LPG)

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Intelligent Systems Design and Applications (ISDA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

In this paper, an approach of principal component analysis (PCA) with local pixel grouping (LPG) is used to de-noising the noisy historical document image. This technique ensures the preservation of historic document image local structure. This is due to block matching based LPG which carries out classification to allow only the sample blocks with similar contents used in the calculation for PCA transform estimation. Such an LPG procedure ensures that the image local features can be well preserved after the noise removing process in the PCA domain. The LPG-PCA de-noising procedure will repeat one more times with adaptively adjusted noise level to further improve the performance of de-noising the historic document image. The experiment results show that LPG-PCA model has good results in de-noising historical document image.

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Acknowledgments

This work was supported by PJP High Impact Research Grant (S01473-PJP/2016/FTMK/HI3) from Universiti Teknikal Malaysia Melaka (UTeM), Malaysia.

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Authors and Affiliations

  1. Computational Intelligence and Technologies Lab (C.I.T Lab), Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM), 76100, Durian Tunggal, Melaka, Malaysia

    Han-Yang Tang, Azah Kamilah Muda, Yun-Huoy Choo, Noor Azilah Muda & Mohd Sanusi Azmi

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  1. Han-Yang Tang
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  2. Azah Kamilah Muda
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  3. Yun-Huoy Choo
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  4. Noor Azilah Muda
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  5. Mohd Sanusi Azmi
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Correspondence to Azah Kamilah Muda .

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Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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Tang, HY., Muda, A.K., Choo, YH., Muda, N.A., Azmi, M.S. (2017). Historic Document Image De-noising Using Principal Component Analysis (PCA) and Local Pixel Grouping (LPG). In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_8

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-53480-0

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