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ITS » Undergraduate Theses » Teknologi Informasi - D4
Posted by system at 17/05/2010 09:46:28  •  3099 Views


TRANSLASI BAHASA ISYARAT

SIGN LANGUAGE TRANSLATION

Created by :
RAKHMAN, JUNIAR PRIMA ( 7405040043 )



SubjectProses gambar
Alt. Subject Image Processing
KeywordDeteksi tangan
deteksi gerakan
klasifikasi gambar
Ekstraksi fitur
deteksi warna kulit

Description:

Masyarakat tuna rungu pada umumnya menggunakan bahasa isyarat sebagai alat komunikasi utamanya. Bahasa isyarat mengutamakan komunikasi visual, pengguna bahasa ini menggunakan orientasi, bentuk dan gerakan tangan, lengan, tubuh, serta expresi wajah untuk mengungkapkan expresi mereka. Tetapi cara komunikasi ini sering menyulitkan/membatasi komunikasi dengan orang lain yang normal, karena perbedaan komunikasinya itu kurang dipahami oleh lawan komunikasinya. Untuk mengatasi keterbatasan komunikasinya tersebut diperlukan upaya penterjemahan bahasa isyarat menjadi lisan. Dengan demikian akan terjadi komunikasi yang lebih mudah antar kaum tuna rungu dengan masyarakat umum. Untuk menyelesaikan proyek akhir ini, digunakan kamera webcam sebaga alat bantu untuk menangkap gambar dari tangan pengguna. Teknik yang digunakan adalah dengan menangkap posisi tangan, mengekstrak bentuk dari tangan tersebut, kemudian mengklasifikasinya. Untuk mencari letak tangan dari setiap frame yang dihasilkan, penulis menggunakan HaarClassifier yang sebelumnya telah dilakukan training terlebih dahulu. Kemudian untuk mengekstrak bentu tangan digunakan skin detection dan noise removal yang kemudian dilanjutkan dengan thresholding dan normalisasi. Setelah bentuk tangan ini didapatkan, maka gambar biner bentuk tangan ini diklasifikasikan berdasarkan kumpulan gambar-gambar isyarat tangan yang digunakan sebagai data training. Algoritma klasifikasi yang digunakan penulis adalah algoritma K Nearest Neigbors. Sistem ini mampu mengenali 19 isyarat huruf tangan dari 26 isyarat yang ditargetkan. Rata-rata akurasi yang dihasilkan system ini adalah 89.68%. Nilai akurasi ini dapat bervariasi tergantung dari konsistensi data training dan noise yang dihasilkan.


Alt. Description

Due to their disability, hearing-impaired uses sign language as their primary means of communication. Sign language uses hand shape, facial expression, and body gesture. However this type of communication is unfamiliar to most people therefore communication between hearing-impaired and normal people can be difficult. There is a need for a system to translate sign language into spoken/written language, so that communication between hearing impaired and normal people can be simplified. To build this final project, the use of web camera is necessary to capture the image of the userís hand. In general this program works by tracking the hand of the user, extract the shape of the hand, and then classify it. To track the position of the hand, we use HaarClassifier that has been trained prior to this project. To extract the hand we use skin detection and noise removal in which the resultan image will then be thresholded and normalized. After the image of the hand shape is extracted, the next step is to classify it by using k nearest neighbor algoritm. Each of the normalized binary images is then converted to feature vector, from this feature vector, distance is measured to find out the majority neighbor in which the new data belongs to. This system able to identify 19 fingerspelling signs out of 26 inteded signs to be identified. The average accuracy for this system is 89.68%. This value can vary depending on the data training consistency dan noise produced.

Contributor:
  1. Nana Ramadijanti, S.Kom, M.Kom
  2. EDI SATRIYANTO, S.SI, M.SI
Date Create:15/02/2010
Type:Text
Format:pdf
Language:Indonesian
Identifier:ITS-Undergraduate-3100010039056
Collection ID:3100010039056
Call Number:RSEP 006.42 Rak t


Source :
Undergraduate thesis, Informatics, RSEP 006.42 Rak t, 2010

Coverage :
ITS Community

Rights :
Copyright @2010 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library


Publication URL :
http://digilib.its.ac.id/translasi-bahasa-isyarat-9843.html




[ Free Download - Free for All ]

  1.  ITS-Undergraduate-9843-translasi-bahasa-isyarat.pdf - 28 KB
  2.  ITS-Undergraduate-9843-sign-language-translation.pdf - 28 KB
  3.  ITS-Undergraduate-9843-Approval_Sheet.pdf - 1231 KB
  4.  ITS-Undergraduate-9843-Abstract_id.pdf - 1572 KB
  5.  ITS-Undergraduate-9843-Abstract_en.pdf - 1470 KB
  6.  ITS-Undergraduate-9843-Preface.pdf - 1939 KB
  7.  ITS-Undergraduate-9843-Table_of_Content.pdf - 24 KB
  8.  ITS-Undergraduate-9843-Tables.pdf - 1230 KB
  9.  ITS-Undergraduate-9843-Illustrations.pdf - 1240 KB
  10.  ITS-Undergraduate-9843-Bibliography.pdf - 6 KB
  11.  ITS-Undergraduate-9843-Biography.pdf - 5 KB
  12.  ITS-Undergraduate-9843-Conclusion.pdf - 8 KB
  13.  ITS-Undergraduate-9843-Presentation.pdf - 777 KB

[ FullText Content - Please, register first ]

  1. ITS-Undergraduate-9843-Chapter2.pdf - 21 KB
  2. ITS-Undergraduate-9843-Chapter2.pdf - 475 KB
  3. ITS-Undergraduate-9843-Chapter3.pdf - 996 KB
  4. ITS-Undergraduate-9843-Chapter4.pdf - 882 KB
  5. ITS-Undergraduate-9843-Chapter5.pdf - 8 KB
  6. ITS-Undergraduate-9843-Enclosure.pdf - 58 KB
  7. ITS-Undergraduate-9843-Enclosure.pdf - 196 KB



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