Abstract
The coarse to fine search methodology is frequently applied to a wide variety of problems in computer vision. In this paper it is shown that this strategy can be used to enhance the recognition of on-line handwritten characters. Some explicit knowledge about the structure of a handwritten character can be obtained through a structural parameterization. The Frame Deformation Energy matching (FDE) method is a method optimized to include such knowledge in the discrimination process. This paper presents a novel parameterization strategy, the Djikstra Curve Maximization (DCM) method, for the segments of the structural frame. Since this method distributes points unevenly on each segment, point-to-point matching strategies are not suitable. A new distance measure for these segment-to-segment comparisons have been developed. Experiments have been conducted with various settings for the new FDE on a large data set both with a single model matching scheme and with a kNN type template matching scheme. The results reveal that the FDE even in an ad hoc implementation is a robust matching method with recognition results well comparing to the existing state-of-the-art methods.
Keywords
- Template Match
- Dynamic Time Warping
- Handwriting Recognition
- Core Point
- Global Transformation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Sternby, J. (2005). Frame Deformation Energy Matching of On-Line Handwritten Characters. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_14
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DOI: https://doi.org/10.1007/11578079_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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