The State of the Art in Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algebraic Description of Curve Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural feature extraction using multiple bases
Computer Vision and Image Understanding
An Algebraic Approach to Automatic Construction of Structural Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
An approach to integration of off-line and on-line recognition of handwriting
Pattern Recognition Letters
Automatic Construction of Structural Models Incorporating Discontinuous Transformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape matching of partially occluded curves invariant under projective transformation
Computer Vision and Image Understanding
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An essential problem in on-line handwriting recognition is the shape variation along with the variety of stroke number and stroke order. In this paper we present a clear and systematic approach to shape matching based on structural feature grouping. To cope with topological deformations caused by stroke connection and breaking, we incorporate some aspects of top-down approaches systematically into the shape matching algorithm. The grouping of local structural features into high-level features is controlled by high-level knowledge as well as the simple geometric conditions. The shape matching algorithm has the following properties from the viewpoint of on-line character recognition: 1) stroke order, direction, and number are free, and 2) stroke connection and breaking are allowed.