Pengenalan Karakter Huruf Braille dengan Metode Convolutional Neural Network

  • Muhammad Fahmi Herlambang Institut Teknologi Nasional Bandung
  • Asep Nana Hermana Institut Teknologi Nasional Bandung
  • Kurnia Ramadhan Putra Institut Teknologi Nasional Bandung
Keywords: Image Processing, Braille Character Recognition, Convolutional Neural Network

Abstract

Braille characters consists of 6 dots that are designed in such way to be a writing system to help blind people. However, learning or reading Braille characters isn’t an easy thing to do, because fingers sensitivity and understanding the writing system are needed to be able to read Braille. Therefore, there are some researches on Braille characters recognition with different methods and technologies, such as deep learning. The Convolutional Neural Network (CNN) is used. CNN method has been used in various recognition researches, such as face recognition, document analysis, image classification, etc. In this research, the CNN method is used to perform Braille characters recognition. The system performs the Braille character recognition process per character based on a model that has been trained using a dataset with the 26 Braille characters. The result of 81.54% accuracy is achieved for Braille character image acquisition with a smartphone with 0 to 4 degrees tilting and 30cm distance with training model using learning rate of 0.0001 and Adam optimizer.

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CROSSMARK
Published
2021-01-27
DIMENSIONS
How to Cite
HerlambangM. F., HermanaA. N., & PutraK. R. (2021). Pengenalan Karakter Huruf Braille dengan Metode Convolutional Neural Network. Systemic: Information System and Informatics Journal, 6(2), 20-26. https://doi.org/10.29080/systemic.v6i2.969
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Articles