On approximating polygonal curves in two and three dimensions
CVGIP: Graphical Models and Image Processing
Self-organizing maps
Skeletons from dot patterns: a neural network approach
Pattern Recognition Letters
Veinerization: A New Shape Description for Flexible Skeletonization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Jump-Diffusion Process for Computing Medial Axes in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and Design of Principal Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal curves: learning, design, and applications
Principal curves: learning, design, and applications
Self-organizing maps for the skeletonization of sparse shapes
IEEE Transactions on Neural Networks
New Approach for the Skeletonization of Handwritten Characters in Gray-Level Images
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Segmentation of black and white cartoons
SCCG '03 Proceedings of the 19th spring conference on Computer graphics
A robust algorithm for image principal curve detection
Pattern Recognition Letters
Handwritten character skeletonisation for forensic document analysis
Proceedings of the 2005 ACM symposium on Applied computing
Statistics and Computing
Three-stage Handwriting Stroke Extraction Method with Hidden Loop Recovery
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Rule-based cleanup of on-line English ink notes
Pattern Recognition
A curve tracing algorithm using level set based affine transform
Pattern Recognition Letters
DBSC-based pencil style simulation for line drawings
Proceedings of the 2006 international conference on Game research and development
Extraction of curvilinear features from noisy point patterns using principal curves
Pattern Recognition Letters
Synthetic handwritten CAPTCHAs
Pattern Recognition
IEEE Transactions on Signal Processing
A neural architecture for the symmetric-axis transform
Neurocomputing
Principal curves with feature continuity
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Techniques for static handwriting trajectory recovery: a survey
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Similarity preserving principal curve: an optimal 1-D feature extractor for data representation
IEEE Transactions on Neural Networks
Locally Defined Principal Curves and Surfaces
The Journal of Machine Learning Research
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
A Skeletonizing Reconfigurable Self-Organizing Model: Validation Through Text Recognition
Neural Processing Letters
Skeleton representation of character based on multiscale approach
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Multiscale approach for thinning ridges of fingerprint
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Axial representation of character by using wavelet transform
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Skeleton extraction for tree models
Mathematical and Computer Modelling: An International Journal
Contour-based shape representation using principal curves
Pattern Recognition
A generative model and a generalized trust region Newton method for noise reduction
Computational Optimization and Applications
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We propose an algorithm to find piecewise linear skeletons of handwritten characters by using principal curves. The development of the method was inspired by the apparent similarity between the definition of principal curves (smooth curves which pass through the "middle" of a cloud of points) and the medial axis (smooth curves that go equidistantly from the contours of a character image). The central fitting-and-smoothing step of the algorithm is an extension of the polygonal line algorithm which approximates principal curves of data sets by piecewise linear curves. The polygonal line algorithm is extended to find principal graphs and complemented with two steps specific to the task of skeletonization: an initialization method to capture the approximate topology of the character, and a collection of restructuring operations to improve the structural quality of the skeleton produced by the initialization method. An advantage of our approach over existing methods is that we optimize the skeleton graph by minimizing an intuitive and explicit objective function that captures the two competing criteria of smoothing the skeleton and fitting it closely to the pixels of the character image. We tested the algorithm on isolated handwritten digits and images of continuous handwriting. The results indicate that the proposed algorithm finds a smooth medial axis of the great majority of a wide variety of character templates and substantially improves the pixelwise skeleton obtained by traditional thinning methods.