Ribbon-like skeletonization based on contour reconstrction on intersection regions
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Skeletonization based on high-level Markov random field
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A blind watermarking scheme using new nontensor product wavelet filter banks
IEEE Transactions on Image Processing
Skeletonization of low-quality characters based on point cloud model
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part IV
An improved contour-based thinning method for character images
Pattern Recognition Letters
K3M: A universal algorithm for image skeletonization and a review of thinning techniques
International Journal of Applied Mathematics and Computer Science
Shape matching and classification using height functions
Pattern Recognition Letters
Multi-feature structure fusion of contours for unsupervised shape classification
Pattern Recognition Letters
A novel free format Persian/Arabic handwritten zip code recognition system
Computers and Electrical Engineering
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Character skeleton plays a significant role in character recognition. The strokes of a character may consist of two regions, i.e., singular and regular regions. The intersections and junctions of the strokes belong to singular region, while the straight and smooth parts of the strokes are categorized to regular region. Therefore, a skeletonization method requires two different processes to treat the skeletons in theses two different regions. All traditional skeletonization algorithms are based on the symmetry analysis technique. The major problems of these methods are as follows. 1) The computation of the primary skeleton in the regular region is indirect, so that its implementation is sophisticated and costly. 2) The extracted skeleton cannot be exactly located on the central line of the stroke. 3) The captured skeleton in the singular region may be distorted by artifacts and branches. To overcome these problems, a novel scheme of extracting the skeleton of character based on wavelet transform is presented in this paper. This scheme consists of two main steps, namely: a) extraction of primary skeleton in the regular region and b) amendment processing of the primary skeletons and connection of them in the singular region. A direct technique is used in the first step, where a new wavelet-based symmetry analysis is developed for finding the central line of the stroke directly. A novel method called smooth interpolation is designed in the second step, where a smooth operation is applied to the primary skeleton, and, thereafter, the interpolation compensation technique is proposed to link the primary skeleton, so that the skeleton in the singular region can be produced. Experiments are conducted and positive results are achieved, which show that the proposed skeletonization scheme is applicable to not only binary image but also gray-level image, and the skeleton is robust against noise and affine transform