Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovery of temporal information from static images of handwriting
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Identification of Fork Points on the Skeletons of Handwritten Chinese Characters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data structures for weighted matching and nearest common ancestors with linking
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovery of Drawing Order from Single-Stroke Handwriting Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Stroke Segmentation Method for Handwritten Chinese Character Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Recovering Writing Traces in Off-Line Handwriting Recognition: Using a Global Optimization Technique
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Recovering Dynamic Information from Static Handwritten Images
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Problem of recovering the writing order from single-stroked handwritten image can be seen as finding the smoothest Euler path in its graph representation. In this paper, a novel approach is proposed to solve the recovery problem within the framework of the Edge Contiguous Relation (ECR). Firstly, we make local analyses to obtain the possible ECRs at each of the nodes; secondly a global trace is executed to find all of the candidate Euler paths and the smoothest one is selected as a final result. Based on two simple assumptions, we prove a series of theorems to obtain possible ECRs at even node. Double-traced lines are identified by using the weighted matching of general graph. Experiments on the scanned images and offline images converted from the online data of Unipen database have shown that our method achieved 95.2% correct recovery rate.