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Using local maxima profile and Piece-Wise technique for line segmentation on Thai handwritten historical documents

Sangsawad, S., Chamchong, R. and Fung, C.C. (2011) Using local maxima profile and Piece-Wise technique for line segmentation on Thai handwritten historical documents. In: International Conference on Machine Learning and Cybernetics, ICMLC 2011, 10 - 13 July, Guilin, China pp. 1862-1866.

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    Link to Published Version: http://dx.doi.org/10.1109/ICMLC.2011.6016974
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    Abstract

    This paper presents a new approach for segmenting text lines on Thai handwritten documents. The proposed technique is based on an Adaptive Local Connectivity Map concept using Piece-Wise Separating Lines. The algorithm is designed to solve problems in handwritten documents such as fluctuating text lines. Moreover, local maxima projection profile is used for enhancing the speed of extraction. The proposed algorithm consists of four steps. Firstly, Otsu algorithm is used to binarize the source image. Second, Piece-Wise Separating Lines is applied to derive the Adaptive Local Connectivity Map to show mask text lines. In the third step, local maxima projection profile is used as a guideline for extracting text lines. Finally, contour algorithm is used to identify the interested mask text line. The interested mask text is used to map with text image in order to extract the text lines. Analysis of experimental results on the King Rama 5 archive data indicated that the method has achieved a correct rate of 85.7%.

    Publication Type: Conference Paper
    Murdoch Affiliation: School of Information Technology
    Publisher: IEEE
    Copyright: © 2011 IEEE
    URI: http://researchrepository.murdoch.edu.au/id/eprint/6015
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