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Farsi Handwritten Phone Number Recognition Using Deep Learning by Maryam Akhlaghi; Vahid Ghods is a Engineering article available to read on EtoBox.

What is Farsi Handwritten Phone Number Recognition Using Deep Learning about?

An application of artificial intelligence in mobile phones which might be widely accepted by users of these phones is the intelligent system used to automatically detect, search and dial phone numbers using an image taken from a handwritten phone number. In this paper, a reliable method is presented for Farsi handwritten phone number recognition using deep neural networks. In order to recognize a Farsi handwritten digit string, the digit string is first converted to single digits using the proposed segmentation algorithm, and then each segment is classified using a single Farsi handwritten digit recognition algorithm. By classifying each segment, finally, the digit string of the Farsi handwritten phone number image is created. Since there is no database for Farsi handwritten phone numbers, this paper first collects a database of Farsi handwritten phone numbers. Accuracy of the proposed algorithm for Farsi handwritten phone number recognition is 94.6%. After recognizing digits of the phone number, the proposed algorithm is able to search in the phonebook.

Who reads Farsi Handwritten Phone Number Recognition Using Deep Learning?

Author

Maryam Akhlaghi; Vahid Ghods

Publisher

Springer-Verlag; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 2523-3963)

Published

2020

Language

EN

Field

Engineering (Physical Sciences)