Pengenalan Huruf Braille Menggunakan Metode Blob Analysis Dan Artificial Neural Network

Subur, Joko (2015) Pengenalan Huruf Braille Menggunakan Metode Blob Analysis Dan Artificial Neural Network. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Huruf braille merupakan jenis huruf yang didesain khusus bagi tuna netra,
tersusun dari enam titik timbul. Enam titik tersebut disusun sedemikian rupa
sehingga menciptakan bermacam kombinasi. Pada umumnya huruf braille di baca
dengan cara diraba dengan telapak tangan, oleh karena itu diperlukan kepekaan
telapak tangan terhadap titik-titik timbul dan harus mengerti serta hafal kombinasi
titik-titik timbul tersebut dalam membentuk suatu huruf. Sehingga tidak semua
orang bisa membaca huruf braille, kebanyakan masih kesulitan dalam membaca
huruf braille. Penelitian ini bertujuan untuk membuat sistem pendeteksi dan
penterjemah karakter braille ke huruf abjad. Digunakan camera webcam untuk
pengambilan gambar huruf braille. Dari gambar huruf braille kemudian diproses
pengolahan citra melalui tahapan croping, grayscale, thresholding, erotion,
dilation, blob analysis dan pengenalan gambar braille menggunakan artificial
neural network. Hasil penelitian ini sistem dapat mengenali karakter braille dan
menterjemahkannya kebentuk huruf abjad dengan tingkat akurasi 99%.

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Braille letter is characters designed for the blind, consist 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 the key issue here. 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, blob analysis and
artificial neural network method are used to recognize the braille characters. The
system can recognize braille characters with 99%.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Artificial neural network, Blob Analysis, Huruf braille, Pengolahan citra, Webcam. =================================================================================================== Artificial neural network, Blob analysis, Braille character, Image processing, Webcam.
Subjects: H Social Sciences > HV Social pathology. Social and public welfare > HV1669 Braille
Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
Divisions: Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User: - Taufiq Rahmanu
Date Deposited: 02 Apr 2019 02:03
Last Modified: 02 Apr 2019 02:03
URI: http://repository.its.ac.id/id/eprint/62670

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