CVGIP: Graphical Models and Image Processing
Recovery of temporal information from static images of handwriting
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Holistic handwritten word recognition using temporal features derived from off-line images
Pattern Recognition Letters
Recognition of off-line cursive handwriting
Computer Vision and Image Understanding
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
A Kalman Approach for Stroke Order Recovering from Off-Line Handwriting
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Recovery of temporal information of cursively handwritten words for on-line recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
A system for scanning and segmenting cursively handwritten words into basic strokes
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Recovery of Drawing Order from Scanned Images of Multi-Stroke Handwriting
ICDAR '99 Proceedings of the Fifth 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
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
Recognition of Cursive Roman Handwriting - Past, Present and Future
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Estimating the Pen Trajectories of Static Signatures Using Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating the Pen Trajectories of Multi-Path Static Scripts Using Hidden Markov Models
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
A Novel Approach to Recover Writing Order From Single Stroke Offline Handwritten Images
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Recovery of a Drawing Order from Off-Line Isolated Letters Dedicated to On-Line Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Recognition-directed recovering of temporal information from handwriting images
Pattern Recognition Letters
A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Verification of dynamic curves extracted from static handwritten scripts
Pattern Recognition
Research of 3d chinese calligraphic handwriting recur system and its key algorithm
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Data-embedding pen: augmenting ink strokes with meta-information
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Techniques for static handwriting trajectory recovery: a survey
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
IWCF'10 Proceedings of the 4th international conference on Computational forensics
Handwriting on paper as a cybermedium
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part IV
Learning Vector Quantisation based recognition of offline handwritten signatures
International Journal of Biometrics
Recovering drawing order of single-stroke handwritten images using probabilistic tabu search
Journal of Mobile Multimedia
More than ink - Realization of a data-embedding pen
Pattern Recognition Letters
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This paper describes a new method to recover a drawing order of a handwritten script from a static 2D image. The script should be written in a single stroke and may include double-traced lines. After the script is scanned in and preprocessed, we apply our recovery method which consists of two phases. In the first phase, we globally analyze the graph constructed from the skeletal image and label the graph by determining the types of each edge. In the second phase, we trace the graph from the start vertex to the end vertex using the labeling information. This method does not enumerate the possible cases, for example, by solving the traveling salesman problem and, therefore, does not cause a combinatorial explosion even if the script is very complex. By recovering a drawing order of a handwritten script, the temporal information can be recovered from a static 2D image. Hence, this method will be used as a bridge from the offline handwriting character recognition problem to the online one.