Recovery of Writing Sequence of Static Images of Handwriting using UWM
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Interfered-Character Recognition by Removing Interfering-Lines and Adjusting Feature Weights
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Estimating the Pen Trajectories of Static Signatures Using Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rule-based cleanup of on-line English ink notes
Pattern Recognition
Verification of dynamic curves extracted from static handwritten scripts
Pattern Recognition
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This paper presents a novel stroke tracing approach to recovering the strokes from the handwriting images. It is carried out not only based on pixel by pixel, but considering the local relation of handwriting strokes. Firstly the primary skeletons of handwriting are produced through the binarization and thinning. Secondly, after the reliable skeletons and unreliable skeletons are classified based on the width information of handwriting, the strokes segments are obtained by the connecting and tracing on the reliable skeletons. Finally, for making the recovered strokes more natural, the post-processing of tracing is discussed. Experimental results show the effectiveness of the approach.