The Recognition Graph - Language Independent Adaptable On-line Cursive Script Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Core Points - A Framework For Structural Parameterization
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Frame deformation energy matching of on-line handwritten characters
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Using strings for on-line handwriting shape matching: a new weighted edit distance
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
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We propose a method derived from an analogy with the primate visual system for selecting the best scale at which the electronic ink of the handwriting should be described. According to this analogy, the method computes a multiscale features maps by evaluating the curvature along the ink at different levels of resolution and arranges them into a pyramidal structure. Then, feature values extracted at different scales are combined in such a way that values that locally stand out from their surrounds are enhanced, while those comparable with their neighbours are suppressed. A saliency map is eventually obtained by combining those features value across all possible scales. Such a map is then used to select a representation that is largely invariant with respect to the shape variations encountered in handwriting. Experiments on two data sets have shown that simple algorithms adopting the proposed representation lead to very stable stroke segmentation and feature matching.