Title :
Using local maxima profile and Piece-Wise technique for line segmentation on Thai handwritten historical documents
Author :
Sangsawad, Seksan ; Chamchong, Rapeeporn ; Fung, Chun Che
Author_Institution :
Sch. of Inf. Technol., Murdoch Univ., Perth, WA, Australia
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%.
Keywords :
document image processing; feature extraction; handwritten character recognition; image segmentation; natural language processing; text analysis; King Rama 5 archive data; Otsu algorithm; Thai handwritten historical document; adaptive local connectivity map concept; contour algorithm; extraction speed; fluctuating text lines; line segmentation; local maxima projection profile; mask text lines; piecewise separating line; source image; text image; Algorithm design and analysis; Cybernetics; Guidelines; Image segmentation; Machine learning; Pattern recognition; Strips; Adaptive Local Connectivity Map (ALCM); Local maxima; Piece-Wise Separating Lines (PSL); Text line extraction; Thai handwritten document;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0305-8
DOI :
10.1109/ICMLC.2011.6016974