A New Textual/Non-Textual Classifier for Document Skew Correction

  • Authors:
  • Xiaoyan Zhu;Xiaoxin Yin

  • Affiliations:
  • -;-

  • Venue:
  • ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
  • Year:
  • 2002

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Abstract

A robust approach is proposed for document skew detection. We use Fourier analysis and SVM to classify textual areas from non-textual areas of documents. We also propose a robust method to determine the skew angle from textual areas. Our approach achieves good performance on documents with large area of non-textual contents.