DocumentCode
2143767
Title
A New Text-Line Alignment Approach Based on Piece-Wise Painting Algorithm for Handwritten Documents
Author
Alaei, Alireza ; Nagabhushan, P. ; Pal, Umapada
Author_Institution
Dept. of Studies in Comput. Sci., Univ. of Mysore, Mysore, India
fYear
2011
fDate
18-21 Sept. 2011
Firstpage
324
Lastpage
328
Abstract
Because of writing styles of different individuals, some of the text-lines may be curved in shape. For recognition of such text-lines, their proper alignment is necessary. In this paper, we propose a text-line alignment technique based on painting algorithm. Here at first, Piece-wise Painting Algorithm (PPA) is used to get a number of black and white rectangular patches all along the text-line for text-line alignment. Identifying the degree of oscillation of the input text-line, some candidate pixels are also obtained based on horizontal projection and center points of the black patches. Using the degree of oscillation of the input text image and the candidate pixels a curve or straight line is fit to trace the baseline. Subsequently, all components of the text-line are deskewed based on analyzing the characteristic of the fit curve or line to align the components with respect to the horizontal imaginary baseline. The proposed algorithm was evaluated with 128 Persian handwritten text-lines containing 4317 sub words. Experimental analysis showed that 92.31% of the sub words were accurately aligned. Further, the proposed algorithm was tested with another Persian handwritten text-lines dataset [6] and remarkable results were achieved.
Keywords
document image processing; edge detection; text analysis; Persian handwritten text-line data set; baseline detection; handwritten document; horizontal projection; piece-wise painting algorithm; text image; text-line alignment approach; Algorithm design and analysis; Curve fitting; Estimation; Oscillators; Painting; Pattern recognition; Polynomials; Curve Fitting; Handwritten Recognition; Linear Regression; Piece-wise Painting Algorithm; Textline alignment;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location
Beijing
ISSN
1520-5363
Print_ISBN
978-1-4577-1350-7
Electronic_ISBN
1520-5363
Type
conf
DOI
10.1109/ICDAR.2011.73
Filename
6065328
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