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    Adaptive document image skew estimation

    Rezaei, S.B.; Shanbehzadeh, J.; Sarrafzadeh, Hossein

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    IMECS2017_pp425_433_Adaptive_Document_Image_Skew_Estimation.pdf (1.514Mb)
    Date
    2017-03
    Citation:
    Rezaei, S.B., Shanbehzadeh, J., & Sarrafzadeh, A. (2017, March). Adaptive document image skew estimation. - (Ed.), International MultiConference of Engineers and Computer Scientists 2017 (IMECS2017) 1, 423-433. http://www.iaeng.org/publication/IMECS2017/IMECS2017_pp425-433.pdf
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/3869
    Abstract
    The skew of the scanned document image is inevitable, and its correction improves the performance of document recognition systems. Skew specifies the text lines deviation from the horizontal or vertical axes. To date, skew estimation algorithms have employed specific features in a repetitive process. We can improve these algorithms by simply using an adaptive algorithm. This approach is suitable when we have large number of similar documents. This paper proposes adaptive document image skew estimation algorithm using the features of existing methods and supervised learning. This approach significantly improves the skew estimation time and accuracy. The time improvement comes from the training that need be performed only once on the training images rather than the repetitive process for each image of previous algorithms. The accuracy improvement comes from the appropriate selection of features, learning algorithm and image adaptively. This method works well in all skew ranges up to 0.1°.
    Keywords:
    scanned document image, skew estimation algorithms, supervised learning, document recognition
    ANZSRC Field of Research:
    0801 Artificial Intelligence and Image Processing
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    http://www.iaeng.org/publication/IMECS2017/IMECS2017_pp425-433.pdf
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    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use. These documents or images may be used for research or private study purposes. Whether they can be used for any other purpose depends upon the Copyright Notice above. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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    • Computing Conference Papers [150]

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