Abstract
When objects are represented by curves in a plane, highly useful information is conveyed by significant points. In this paper, we compare the use of different mobile windows to extract dominant points of handwritten characters. The error rate and classification time using an edit distance based nearest neighbour search algorithm are compared for two different cases: string and tree representation.
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Rico-Juan, J.R., Micó, L. (2004). Finding Significant Points for a Handwritten Classification Task. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_55
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DOI: https://doi.org/10.1007/978-3-540-30125-7_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23223-0
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