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Farsi and Arabic document images lossy compression based on the mixed raster content model

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Abstract

Recently, the mixed raster content model was proposed for compound document image compression. Most state-of-the-art document image compression methods, such as DjVu, work on the basis of this model but they have some disadvantages, especially for Farsi and Arabic document images. First, the Farsi/Arabic script has some characteristics which can be used to further improve the compression performance. Second, existing segmentation methods have focused on well-separating the textual objects from the background and/or optimizing the rate-distortion trade-off; nevertheless, they have not considered the text readability and OCR facility. Third, these methods usually suffer from the undesired jaggy artifact and misclassifying the important textual details. In this paper, MRC-based document image compression method is proposed which compromises rate-distortion trade-off better than the existing state-of-the-art document compression methods. The proposed method has higher performance in the aspects of segmentation, bi-level mask layer compression, OCR facility, and the overall compression. It uses a 1D pattern matching technique for compression of mask layer. It also uses a segmentation method which is sensitive enough to the small textual objects. Experimental results show that the proposed method has considerably higher compression performance than that of the state-of-the-art compression method DjVu, as high as 1.75–2.3.

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Authors and Affiliations

  1. Department of Electrical Engineering, Tarbiat Modares University, Tehran, Iran

    Hadi Grailu & Mojtaba Lotfizad

  2. Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Hadi Sadoghi-Yazdi

Authors
  1. Hadi Grailu
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  2. Mojtaba Lotfizad
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  3. Hadi Sadoghi-Yazdi
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Corresponding author

Correspondence to Mojtaba Lotfizad.

Additional information

This work was supported by the Iranian Telecommunication Research Center (ITRC) under the granted number TMU87-06-30.

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Grailu, H., Lotfizad, M. & Sadoghi-Yazdi, H. Farsi and Arabic document images lossy compression based on the mixed raster content model. IJDAR 12, 227–248 (2009). https://doi.org/10.1007/s10032-009-0088-6

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  • DOI: https://doi.org/10.1007/s10032-009-0088-6

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