Penerjemah Citra Braille Dasar Berbasis Web dengan Segmentasi YOLOv8 dan Klasifikasi CNN

Authors

  • Arie Nurjannah Universitas Nusantara PGRI Kediri Indonesia
  • Made Ayu Dusea Widyadara Universitas Nusantara PGRI Kediri Indonesia
  • Daniel Swanjaya Universitas Nusantara PGRI Kediri Indonesia

DOI:

https://doi.org/10.29407/dpzngy15

Abstract

Kemampuan membaca Braille tidak hanya diperlukan oleh guru, tetapi juga oleh orang tua yang mendampingi anak tunanetra belajar di rumah. Kendala yang sering muncul adalah pola titik Braille timbul memiliki kontras rendah sehingga sulit dibaca oleh orang tua yang belum terbiasa. Penelitian ini bertujuan mengembangkan sistem bantu baca Braille karakter dan suku kata berbasis web untuk menerjemahkan citra Braille menjadi huruf Latin, suku kata, kata, dan suara pembelajaran. Sistem dibangun menggunakan Flask sebagai kerangka web, OpenCV untuk koreksi perspektif gambar, YOLOv8 untuk segmentasi suku kata, dan CNN untuk klasifikasi karakter. Data keluaran model kemudian diproses kembali melalui aturan pengelompokan konsonan-vokal agar hasil karakter dapat dibaca sebagai suku kata sederhana, misalnya b + u menjadi bu dan bu + ku menjadi buku. Hasil implementasi menunjukkan bahwa sistem mampu menerima input melalui unggah gambar maupun kamera, menampilkan grid suku kata, serta membacakan naskah pembelajaran dengan sinkronisasi animasi grid. Sistem ini relevan digunakan sebagai media bantu awal bagi orang tua anak tunanetra, meskipun performa prediksi masih bergantung pada kualitas foto, pencahayaan, posisi kertas, dan model yang digunakan.

Keywords:

Braille, CNN, Flask, sistem bantu baca, suku kata, YOLOv8

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References

[1] W. H. Organization, ―Blindness and vision impairment,‖ World Health Organization,

2026.

[2] M. Abadi, ―TensorFlow: A system for large-scale machine learning,‖ in Proceedings of

the 12th USENIX Symposium on Operating Systems Design and Implementation, 2016,

pp. 265–283.

[3] I. M. A. D. Suarjaya, B. A. Wiratama, and A. Wirdiani, ―Sistem Pengenalan Huruf

Braille Menggunakan Metode Deep Learning Berbasis Website,‖ Jurnal Ilmiah

Teknologi Sistem Informasi, vol. 5, no. 3, pp. 93–99, 2024, doi: 10.62527/jitsi.5.3.244.

[4] Y. LeCun, Y. Bengio, and G. Hinton, ―Deep learning,‖ Nature, vol. 521, pp. 436–444,

2015, doi: 10.1038/nature14539.

[5] T. V. Y. G. Setiawan and E. H. Rachmawanto, ―A Two-Stage Braille Recognition

System Using YOLOv8 for Detection and CNN for Classification,‖ Journal of Applied

Informatics and Computing, vol. 9, no. 6, 2025, doi: 10.30871/jaic.v9i6.11483.

[6] Z. Meng, Z. Cai, J. Feng, H. Ma, H. Zhang, and S. Li, ―Braille Character Segmentation

Algorithm Based on Gaussian Diffusion,‖ Computers, Materials & Continua, vol. 79,

no. 1, pp. 1481–1496, 2024, doi: 10.32604/cmc.2024.048002.

[7] J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, ―You Only Look Once: Unified,

Real-Time Object Detection,‖ in Proceedings of the IEEE Conference on Computer

Vision and Pattern Recognition, 2016, pp. 779–788.

[8] A. Ridwan, Y. Purbolingga, and Hanisah, ―Utilizing Convolutional Neural Network for

Learning Web-Based Braille Letter Classification System,‖ Journal of Computer

Networks, Architecture and High Performance Computing, vol. 6, no. 1, 2024, doi:

10.47709/cnahpc.v6i1.3386.

[9] I. G. Ovodov, ―Optical Braille Recognition Using Object Detection CNN,‖ 2020.

[10] G. Bradski, ―The OpenCV Library,‖ Dr. Dobb’s Journal of Software Tools, 2000

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Published

2026-07-20

Issue

Vol. 10 No. 2 (2026): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2026

Section

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How to Cite

Penerjemah Citra Braille Dasar Berbasis Web dengan Segmentasi YOLOv8 dan Klasifikasi CNN. (2026). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 10(2), 1616-1625. https://doi.org/10.29407/dpzngy15