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Piece-wise painting technique for line segmentation of unconstrained handwritten text: a specific study with Persian text documents

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Abstract

The most important and difficult task in text document analysis is to achieve line segmentation accurately, particularly when the document is composed of unconstrained handwritten text. To accomplish this objective a painting scheme is proposed in this research work. Being motivated by the fact that the handwritten Persian texts offer the most critical challenges in the process of text-line segmentation, the new method has been devised by studying the cursive Persian text scripts extensively; yet, in general the proposed line segmentation algorithm is applicable to handwritten text in any language/script. The text block is vertically decomposed into parallel pipe structures called as strip. Each row in each strip is painted by a gray intensity, which is the average intensity value of gray values of all pixels present in that row-strip. Subsequently, the painted pipes are converted into two-tone painting and it is smoothed. The white/black spaces in each pipe of the smoothed image are analyzed to get a short line of separation, phrased as Piece-wise Potential Separating Line (PPSL), between two consecutive black spaces. The PPSLs are concatenated to produce the segmentation of text lines. Some additional procedures are built to handle certain anomalies, which may occur. The scheme is validated by extensive experimentation. We tested the proposed algorithm with 52 pages of Persian text documents containing totally 823 lines and correct line segmentation of 92.35% is achieved. Moreover, the proposed algorithm was also tested with two different datasets of 152 and 200 handwritten text-pages of different languages. Efficiency and script independency of the proposed algorithm were proved when compared with various approaches presented in recent literature.

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Authors and Affiliations

  1. Department of Studies in Computer Science, University of Mysore, Manasagangotri, Mysore, 570 006, Karnataka, India

    Alireza Alaei & P. Nagabhushan

  2. Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, B.T. Road, Kolkata, 108, West Bengal, India

    Umapada Pal

Authors
  1. Alireza Alaei
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  2. P. Nagabhushan
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  3. Umapada Pal
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Corresponding author

Correspondence to Alireza Alaei.

Appendix: contributions in this paper

Appendix: contributions in this paper

Line segmentation from unconstrained handwritten document is a difficult task because of the writing styles of different individuals. Characters of two consecutive text lines may touch or overlap and such touching/overlapping makes the line segmentation task more complex. In this paper, a painting scheme is proposed to facilitate unconstrained handwritten text-line segmentation process. In the proposed scheme, input text page is vertically decomposed into parallel pipe structures called as strip. The width of strips is automatically computed based on the space (gap) between the consecutive lines in each text-page. Each row of a strip is painted by a gray intensity, which is the average intensity value of gray values of all pixels present in that row-strip. The painted strips are then converted into two-tone painting image and using some smoothing operations the two-tone painted image is smoothed. The white/black spaces in each pipe of the smoothed image are analyzed to get a short line of separation, called as Piece-wise Potential Separating Line (PPSL), between two consecutive black spaces. Finally, the PPSLs are concatenated or extended for text-line separation. The proposed method can also handle touching/overlapping cases. To do so, the proposed system initially detects the touching/overlapping zones and then based on the structural behavior of such zones, they are segmented.

The scheme is validated by extensive experimentations with many scripts. The proposed algorithm was tested with 52 pages of Persian text documents containing totally 823 lines and 92.35% line segmentation accuracy was achieved. Moreover, the proposed algorithm was tested with two different datasets containing 152 and 200 handwritten text-pages of different languages such as English, Greek, French, and German. Efficiency and script independency of the proposed algorithm was proved when compared with various approaches presented in recent literature.

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Alaei, A., Nagabhushan, P. & Pal, U. Piece-wise painting technique for line segmentation of unconstrained handwritten text: a specific study with Persian text documents. Pattern Anal Applic 14, 381–394 (2011). https://doi.org/10.1007/s10044-011-0226-x

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