Farsi handwritten phone number recognition using deep learning

被引:9
|
作者
Akhlaghi, Maryam [1 ]
Ghods, Vahid [2 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Semnan Branch, Semnan, Iran
[2] Islamic Azad Univ, Semnan Branch, Young Researchers & Elite Club, Semnan, Iran
来源
SN APPLIED SCIENCES | 2020年 / 2卷 / 03期
关键词
Phone number; Recognition; Farsi; Convolutional neural network; Segmentation;
D O I
10.1007/s42452-020-2222-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:10
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