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25 September 2003 Page segmentation and classification algorithm for skewed document images with graph regions
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Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539076
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China
Abstract
In this paper, a system for the segmentation and classification of the skewed document images with graph regions is proposed. In this system, the skewed angles of the document images are detected with a novel algorithm based on the morphological operation of Hit-or-Miss and the Hierarchical Hough transformation. To make the system valid for document images with graph regions, we proposed to introduce a middle point cut process to the traditional recursive X-Y cuts (RXYC) segmentation algorithm so that the graph regions can be approximated with a lot of small rectangles. The segmented regions are classified by two features of BWR and CC, which represent respectively the black to white pixel ratio and the cross-correlation between pixels of the sub-blocks. Experimental results have proved the fastness and the reliability of the system proposed in this paper.
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Jiajun Wang, Xianwu Huang, Xingrong Zhong, and Weiwei Guo "Page segmentation and classification algorithm for skewed document images with graph regions", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539076
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