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All Journal IPTEK Journal of Proceedings Series PROtek : Jurnal Ilmiah Teknik Elektro CYCLOTRON TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan JAVA Journal of Electrical and Electronics Engineering Elektrika Borneo Journal Zetroem Journal of Electrical Engineering and Computer (JEECOM) JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) As-Sidanah : Jurnal Pengabdian Masyarakat Proceedings Series on Physical & Formal Sciences SinarFe7 Jurnal Borneo Informatika dan Teknik Komputer (JBIT) JPMP Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Joko Subur
Universitas Hang Tuah
Religion Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Journal : JAVA Journal of Electrical and Electronics Engineering

 1 
Braille Character Recognition Using Find Contour And Artificial Neural Network Subur, Joko; Sardjono, Tri Arief; Mardiyanto, Ronny
JAVA Journal of Electrical and Electronics Engineering Vol 14, No 1 (2016)
Publisher : JAVA Journal of Electrical and Electronics Engineering

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Abstract

Abstract—Braille letters is characters designed for the blind, composed of six embossed points, arranged in a standard braille character. Braille letters is touched and read using fingers, therefore the sensitivity of the fingers is important. Those characters need to be memorized, so it is very difficult to be learned. The aim of this research is to create a braille characters recognition system and translate it to alpha-numeric text. Webcam camera is used to capture braille image from braille characters on the paper sheet. Cropping, grayscale, thresholding, erotion, and dilation techniques are used for image preprocessing. Then, find contour and artificial neural network method are used to recognize the braille characters. The system can recognize braille characters with 99% accuracy even when the braille image is tilted up to 1 degrees. Keywords— Artifial neural network; braille characters; find contour; image processing; webcam
Co-Authors Aditya, Bagus Kusuma Afrizal Septiano Arisandi Ari Muhammad Rizal Arohman, Eki Cholid Kusyairi Cholid Kusyairi Daud Saputro, Dimas Hutomo Dimas Hutomo Daud Saputro Faqri Wijayanto Amaral, Fauzan Hartoyo Hartoyo Herman Herman Kristiyono, Tri Agung Lailul Ahada Lailul Ahada M Taufiqurrohman Muh. Taufiqurrohman Muh. Taufiqurrohman Muh. Taufiqurrohman Muh. Taufiqurrohman, S.T., M.T. Muhammad Taufiqurrohman Muhammad Taufiqurrohman Muhammad Taufiqurrohman, Muhammad Nirmalasari Idha Wijaya Novian Reza Al Hafizh Nuhman, Nuhman Nurul Rosana, Nurul Rahmatullah, Daeng Ramdahani, Aditya Reza Al Hafizh, Novian Rifandi, Safriudin Ronny Mardiyanto, Ronny Rudi S Bintoro Setya Prihatiningtyas Sirrulah Putriani Sirrulah Putriani Suryadhi Suryadhi Suryadhi - Suryadhi Suryadhi, Suryadhi Taufiqurrohman, M Taufiqurrohman, Muh. Tri Arief Sardjono Vila, Vila Puspita Devi Wicaksono, Agung Rizaldi Widagdo, Supriyatno Widyadharma, Indra Wienta Diarsvitri Yudistira Yusan, Liza