Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Segmentation of page images using the area Voronoi diagram
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
Recognition-based handwritten Chinese character segmentation using a probabilistic Viterbi algorithm
Pattern Recognition Letters
Binarization of historical document images using the local maximum and minimum
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
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In this paper, we present the first effort in preprocessing and character segmentation on digitized Nom document pages toward their digital archiving. Nom is an ideographic script to represent Vietnamese, used from the 10th century to 20th century. Because of various complex layouts, we propose an efficient method based on connected component analysis for extraction of characters from images. The area Voronoi diagram is then employed to represent the neighborhood and boundary of connected components. Based on this representation, each character can be considered as a group of extracted adjacent Voronoi regions. To improve the performance of segmentation, we use the recursive x-y cut method to segment separated regions. We evaluate the performance of this method on several pages in different layouts. The results confirm that the method is effective for character segmentation in Nom documents.