Abstract
We propose a new method for natural writing recognition that utilizes geometric features of letters. The paper deals with recognition of isolated handwritten characters using an artificial neural network. As a result of the geometrical analysis realized, graphical representations of recognized characters are obtained in the form of pattern descriptions of isolated characters. The radius measurements of the characters obtained are inputs to the neural network for natural writing recognition which is font independent. In this paper, we present a new method for off-line natural writing recognition and also describe our research and tests performed on the neural network.
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Kacalak, W., Majewski, M. (2012). Effective Handwriting Recognition System Using Geometrical Character Analysis Algorithms. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34478-7_31
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DOI: https://doi.org/10.1007/978-3-642-34478-7_31
Publisher Name: Springer, Berlin, Heidelberg
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