Artificial Intelligence
Partial Shape Classification Using Contour Matching in Distance Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Based Detection of Corners of Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
False stroke detection and elimination for character recognition
Pattern Recognition Letters
On the Generation of Skeletons from Discrete Euclidean Distance Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Derived From B-Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Piecewise Linear Skeletonization Using Principal Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skeletonization of Ribbon-Like Shapes Based on a New Wavelet Function
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Analysis of stroke structures of handwritten Chinese characters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Characterization of Dirac-structure edges with wavelet transform
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Skeletonization of ribbon-like shapes based on regularity andsingularity analyses
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiscale corner detection by using wavelet transform
IEEE Transactions on Image Processing
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Axial representation plays a significant role in character recognition. The strokes of a character may consist of two regions, i.e. singular and regular regions. Therefore, a method to extract the central axis of a character requires two different processes to compute the axis in theses two different regions. The major problem of most traditional algorithms is that the extracted central axis in the singular region may be distorted by artifacts and branches. To overcome this problem, the wavelet-based amendment processing technique is developed to link the primary axis, so that the central axis in the singular region can be produced. Combining with our previously developed method for computing the primary axis in the regular region, we develop a novel scheme of extracting the central axis of character based on the wavelet transform (WT). Experimental results show that the final axis obtained from the proposed scheme closely resembles the human perceptions. It is applicable to both binary image and gray-level image as well. The axis representation is robust against noise.