JOURNAL ARTICLE

Braille Identification System Using Artificial Neural Networks

Mohammed Waleed

Year: 2023 Journal:   Tikrit Journal of Pure Science Vol: 22 (2)Pages: 140-145

Abstract

The Braille system is a widely used method by the blind to read and write. Information technology revolution is changing the way Braille reading and writing, making it easier to use. All kinds of materials can be put into Braille representation, such as bank statements, bus ticket, maps, and music note. In this paper, an artificial neural networks are designed to identify the number's image from (0-9) in Braille representation system. Networks will be trained and tested to be used for identify the scanned English number in Braille representation system. Some of the numbers are noised with some type of noise to simulate somehow the real world environment. According to the experiment the result of the identification of number that written in Braille representation using Artificial Neural Networks the training accuracy was 97.1% and testing accuracy was 85%.

Keywords:
Braille Computer science Artificial neural network Representation (politics) Identification (biology) Reading (process) Artificial intelligence Speech recognition Ticket Noise (video) Natural language processing Image (mathematics) Linguistics

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
6
Refs
0.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Hand Gesture Recognition Systems
Physical Sciences →  Computer Science →  Human-Computer Interaction
Tactile and Sensory Interactions
Life Sciences →  Neuroscience →  Cognitive Neuroscience
Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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