Abstract
Automatic handwriting recognition plays a crucial role because writing with a pen is the most common and natural input method for humans. Whereas many algorithms detect the writing after finishing the input, this paper presents a handwriting recognition system that processes the input data during writing and thus detects misspelled characters on the fly from their origin.
The main idea of the recognition is to decompose the input data into defined structures. Each character can be composed out of the structures point, line, curve, and circle. While the user draws a character, the digitized points of the pen are processed successively, decomposed into structures, and classified with the help of samples. The intermediate classification allows a direct feedback to the user as soon as the input differs from a given character.
This work has been partially funded by the ERC within the starting grant Dynamic MinVIP.
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Reinders, C. et al. (2015). On-The-Fly Handwriting Recognition Using a High-Level Representation. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_1
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DOI: https://doi.org/10.1007/978-3-319-23192-1_1
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