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Document Layout Analysis Based on Fuzzy Energy Matrix

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초록

In this paper, we describe a novel method for document layout analysis that is based on a Fuzzy Energy Matrix (FEM). A FEM is a two-dimensional matrix that contains the likelihood of text and non-text and is generated through the use of Fuzzy theory. The key idea is to define an Energy map for the document to categorize text and non-text. The proposed mechanism is designed for execution with a low-resolution document image, and hence our method has a fast processing speed. The proposed method has been tested on public ICDAR 2009 datasets to conduct a comparison against other state-of-the-art methods, and it was also tested with Korean documents. The results of the experiment indicate that this scheme achieves superior segmentation accuracy, in terms of both precision and recall, and also requires less time for computation than other state-of-the-art document image analysis methods.

Abstract

In this paper, we describe a novel method for document layout analysis that is based on a Fuzzy Energy Matrix (FEM). A FEM is a two-dimensional matrix that contains the likelihood of text and non-text and is generated through the use of Fuzzy theory. The key idea is to define an Energy map for the document to categorize text and non-text. The proposed mechanism is designed for execution with a low-resolution document image, and hence our method has a fast processing speed. The proposed method has been tested on public ICDAR 2009 datasets to conduct a comparison against other state-of-the-art methods, and it was also tested with Korean documents. The results of the experiment indicate that this scheme achieves superior segmentation accuracy, in terms of both precision and recall, and also requires less time for computation than other state-of-the-art document image analysis methods.

참고문헌 (13)

  1. P. Bhupendra Kumar, "Integrated Fuzzy-HMM for project uncertainties in time-cost tradeoff problem", J. Applied Soft Computing, 21, pp.320~329 (2014)
  2. S. M. Chen, "Forecasting enrollments based on fuzzy time series", Fuzzy Sets and Systems, 81, pp.311~319 (1996)
  3. N. Otsu, "A Threshold Selection method from Gray Level Histogram", IEEE Transactions on Systems, Man and Cybernetics, 9(1), pp.62~66 (1975)
  4. J. Sauvola, "Adaptive document image binarization", J. The Journal of the Pattern Recognition, pp.225~236 (2000)
  5. A. Fletcher, "A robust algorithm for text string separation from mixed text", graphics images, 1998, pp.10, 294~308
  6. K. J. Anil, "Document representation and its application to page decomposition", IEEE Trans. Pattern Anal. Mach. Intell, 20, pp.294~308 (1998)
  7. D. L. O’Gorman, "The document spectrum for page layout analysis", IEEE Trans. Pattern Anal. Mach. Intell, 15, pp.1162~1173 (1993)
  8. C. Laura, "Document page segmentation using neuro-fuzzy approach", Applied Soft Computing, 8, pp.118~126 (2008)
  9. K. Kise, "Segmentation of page images using the area Voronoi diagram", In Computer Vision Image Understanding, 70(3), pp.370~382 (1998)
  10. D. H. S. Baird, "Backgroud structure in document images", Int. J. Pattern Recognition Artif. Intell, 8, pp.1013~1030 (1994)
  11. K. J. Anil, "Document representation and its application to pagedecomposition", IEEE Trans. Pattern Anal. Mach. Intell, 20, pp.294~308 (1998)
  12. A. Antonacopoulos, "ICDAR2009 Page Segmentation Competition", Proc. ICDAR, pp.1370~1374 (2009)
  13. Ray Smith, "Hybrid Page Layout Analysis via Tab -Stop Detection", Proc. ICDAR, Barcelona, Spain, pp.241~245 (2009)

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