Abstract
Optical Character Recognition software (OCR) are important tools for obtaining accessible texts. We propose the use of artificial neural networks (ANN) in order to develop pattern recognition algorithms capable of recognizing both normal texts and formulae. We present an original improvement of the backpropagation algorithm. Moreover, we describe a novel image segmentation algorithm that exploits fuzzy logic for separating touching characters.
R. Rossini—This work has been developed in the framework of an agreement between IRIFOR/UICI (Institute for Research, Education and Rehabilitation/Italian Union for the Blind and Partially Sighted) and Turin University.
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Farulla, G.A., Armano, T., Capietto, A., Murru, N., Rossini, R. (2016). Artificial Neural Networks and Fuzzy Logic for Recognizing Alphabet Characters and Mathematical Symbols. In: Miesenberger, K., Bühler, C., Penaz, P. (eds) Computers Helping People with Special Needs. ICCHP 2016. Lecture Notes in Computer Science(), vol 9758. Springer, Cham. https://doi.org/10.1007/978-3-319-41264-1_1
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