On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
The shape of handwritten characters
Pattern Recognition Letters
Lexical Post-Processing Optimization for Handwritten Word Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Design and integration of a handwritten character recognition system into mobile phones
UbiMob '04 Proceedings of the 1st French-speaking conference on Mobility and ubiquity computing
ECML '07 Proceedings of the 18th European conference on Machine Learning
Teaching a humanoid robot to draw `Shapes'
Autonomous Robots
Effect of perceptual anchorage points on recognition of bangla characters
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
HBF49 feature set: A first unified baseline for online symbol recognition
Pattern Recognition
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A new handwriting modeling and segmentation approach is introduced for cursive letter and word analysis. For the letter analysis, the proposed method is based on the detection of a set of "perceptual anchorage points" to extract a priori pertinent strokes. This physical segmentation of the handwritten drawing enables us to conduct a logical modeling of letters with respect to the most stable strokes of each letter class. For the handwritten word analysis we present a constructive segmentation approach to overcome the word segmentation problem. The main idea is to locate "anchorage structures" in the word drawing based on the most robust strokes of the letters. This new approach of handwriting analysis has been implemented in a writer independent on-line handwriting recognition system. Experimental results are reported using a lexicon context of 1128, 7000 and 25000 words.