On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Piecewise Linear Modulation Model of Handwriting
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Why Handwriting Segmentation Can Be Misleading?
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Learning-based Cursive Handwriting Synthesis
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Structure in On-line Documents
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Generation of Synthetic Training Data for an HMM-based Handwriting Recognition System
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Handwriting Trajectory Movements Controlled by a Bêta-Elliptic Model
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Generation of Handwritten Characters with Bayesian network based On-line Handwriting Recognizers
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Design and analysis of delimiters for selection-action pen gesture phrases in scriboli
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Combining shape and physical modelsfor online cursive handwriting synthesis
International Journal on Document Analysis and Recognition
Analysis and modeling of naturalness in handwritten characters
IEEE Transactions on Neural Networks
Synthetic on-line signature generation. Part I: Methodology and algorithms
Pattern Recognition
Computer Vision and Image Understanding
A novel hand reconstruction approach and its application to vulnerability assessment
Information Sciences: an International Journal
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This paper presents a novel and effective approach to synthesize English handwriting in the user's writing style. We select the most important features that depict the handwriting style, including character glyph, size, slant, and pressure, special connection style, letter spacing, and cursiveness. The features can be efficiently computed with the aid of our specially designed sample collecting user interface. Given ASCII text, the user handwriting is synthesized hierarchically. First, character glyphs are sampled and shape variation is added. Second, words are generated by aligning the character glyphs on the baseline with proper horizontal inter-character space and vertical offset from the baseline. The heads and tails of the letters may be trimmed to avoid severe overlap and facilitate possible connections between neighboring letters. Adjacent letters may be connected to each other by polynomial interpolation. Finally, after the pressure is assigned, the handwriting is rendered word by word and then line by line. The experimental results prove the capability of our system to adapt to the user's writing style.