An Arabic Optical Braille Recognition System

Technology has shown great promise in providing access to textual information for visually impaired people. Optical Braille Recognition (OBR) allows people with visual impairments to read volumes of typewritten documents with the help of flatbed scanners and OBR software. This project looks at developing a system to recognize an image of embossed Arabic Braille and then convert it to text. It particularly aims to build fully functional Optical Arabic Braille Recognition system. It has two main tasks, first is to recognize printed Braille cells, and second is to convert them to regular text. Converting Braille to text is not simply a one to one mapping, because one cell may represent one symbol (alphabet letter, digit, or special character), two or more symbols, or part of a symbol. Moreover, multiple cells may represent a single symbol

Experience of Using the Angelina Braille Reader Program for Inclusive Education of Blind Children

В статье описывается опыт применения сервиса оптического распознавания шрифта Брайля "Angelina Braille Reader" для организации обучения слепых и слабовидящих детей.This paper describes the experience of using the Angelina Braille Reader optical Braille recognition service for the organization of education for blind children, including distance learning. The use of this service allows teachers who know only the basics of Braille writing to work with blind children. It also makes it possible to send the teacher a handwritten work written by a student in Braille, in the form of a photo. Reading Braille text from a photo with your eyes is a particularly difficult task even for a professional, but the technology used allows the teacher to do this. Typhlo¬pedagogues can read Braille text much faster and without straining their eyes

A robust braille recognition system

Braille is the most effective means of written communication between visually-impaired and sighted people. This paper describes a new system that recognizes Braille characters in scanned Braille document pages. Unlike most other approaches, an inexpensive flatbed scanner is used and the system requires minimal interaction with the user. A unique feature of this system is the use of context at different levels (from the pre-processing of the image through to the post-processing of the recognition results) to enhance robustness and, consequently, recognition results. Braille dots composing characters are identified on both single and double-sided documents of average quality with over 99% accuracy, while Braille characters are also correctly recognised in over 99% of documents of average quality (in both single and double-sided documents)

The impact of different reading/writing media on the education and employment of blind persons

Particularly in recent years, prompted by the need to gain greater independent access to a wider range of information, many persons who are blind make extensive use of screen access technology, optical character recognition devices, refreshable Braille displays and electronic notetakers in a variety of contexts. These reading and writing media have proved to be so useful and effective, raising debates in the literature on whether there is a decline in the use of Braille, or whether Braille as a reading and writing medium would become obsolete. Following a discussion on the development of tactual reading and writing media as part of an historical background to blindness, as well as an evaluation of the various reading and writing media used in South Africa by persons who are blind, this study, using a quantitative approach with a survey design, aimed to determine the impact of the various reading and writing media on the education and employment of persons who are blind. Based on the findings of the study, what emerges forcefully with regard to the preference of a medium for reading or writing is that a greater number of persons who are blind prefer Braille and computers with speech output. Notwithstanding this, there is support for the need to provide instruction in the use of the various reading and writing media, highlighting the critical value and role of the various media. Additionally, while persons who are blind appear to be convinced that computers will not replace Braille, they were, however, divided on whether there is a decline in the use of Braille, and whether computers would replace audiotapes. Finally, conclusions, based mainly on the findings of the study are drawn, and recommendations, both for future research, and for an integrated reading and writing model, are made.Educational StudiesD.Ed.(Special Needs Educstion

Translasi pada Image Document braille Indonesia ke text Bahasa Indonesia dengan menggunakan Optical Braille Recognition (OBR)

ABSTRAKSI: Abstrak Optical Braille Recognation adalah sistem komputer yang mampu membaca sebuah dokumen braille yang telah menjadi image. OBR membantu dalam proses pengecekan tulisan braille yang telah di ketik di dokumen agar lebih efektif dalam segi waktu dan tenaga.Di sistem ini di bangun menggunakan beberapa metode. Metode dalam OBR di sistem ini terdiri dari beberapa metode termasuk image acquisition yaitu memasukan image, image processing, dot localization, dot recognition and conversion dan pada dot localization menggunakan grid calculation,grid calculation disini menggunakan kurva vertikal dan horizontal dimana kurva tersebut di gunakan untuk memposisikan dot dot braille dan dot recognition menggunakan mesh detection, mesh detection disini merupakan metode untuk merubah dot dot braille untuk dinyatakan aktif atau tidaknya. Dan conversion dilakukan ketika semua posisi titik braille sudah di dapat maka akan di ubah ke menjadi biner lalu di ubah menjadi angka dan akan dicocok kan dengan database huruf alfabeth dengan menggunakan decimal code generation dan matching algorithmBerdasarkan pengujian yang dilakukan dengan menerapkan metode grid calculation, mesh detection, decimal code generation pada image dokumen braille di dalam sistem OBR ini, hasil pengujian bisa dilihat dari akurasi perhuruf dan perdot braillenya untuk akurasi perhuruf 97,54% dan per dot braillenya 99,58%. Dari pengujian yang dilakukan kualitas kertas dan pengetikan dot dot braille menjadi faktor yang mempengaruhi tingkat pendeteksian titik titik yang aktif maupun yang tidak aktifnya suatu dot dot braille.Kata Kunci : OBR, grid calculation, mesh detection, decimal code generation,ABSTRACT: Optical Braille recognation is a computer system capable of reading a document that has into braille image. OBR assist in the process of writing checks on the baille writing that has been typed in the document to be more effective in terms of time and effort.In this system built by using multiple methods. OBR Methods in this system consists of a number of methods including image acquisition that include image, image processing, dot localization, dot recognition and conversion, and the dot localization using grid calculation, grid calculation here using vertical and horizontal curves where curves are used to position braille dot and dot recognition using a mesh detection,mesh detection here is a method to change the dot dot braille to be declared active or not. And the conversion done when all dot positions are recive then it changed into a binary then converted into numbers and it matched with the alfabeth database using a decimal code generation and matching algorithmBased on testing performed by applying the method of grid calculation, mesh detection, decimal code generation on the image document braille in OBR system, the test results can be seen from the accuracy by alfabeth and by dot for alfabeth accuracy is 97,54% and dot braille is 99,58%. From the tests performed the paper quality and dot braille typing have the factors affecting the level of detection of the points are active or not active a dot dot braille.Keyword: OBR, grid calculation, mesh detection, decimal code generation

Aplikasi Identifikasi Huruf Braille Menggunakan Computer Vision Berbasis Raspberry Pi

Sense of vision is a source of information on humans. Some humans are created with limited sense of sight. The blind performs reading and writing activities using Braille letters, a printed code system consisting of six dots in various combinations that are highlighted on the paper so that they can be touched. To facilitate the visually impaired and the public in enjoying the works produced by blind people, a script reading system is characterized by Braille by studying the braille characters in advance of each character. This research makes a braille letter identification system into sound using computer vision. The method, the reading of Braille character scripts by studying braille characters. First, a scanner or Raspberry Pi-based camera captures braille characters. Second, the system converts Braille characters into alphabetical shapes by processing Optical Character Recognition images. Recognition of Braille character patterns in written text using Artificial Neural Networks. The results of research on braille testing are in the form of alphabetical texts a through z, and the sound signal of the pronunciation of the alphabet uses the Text To Speech system. Braille to sound conversion system works well, with an average accuracy of system testing of 88.462%. This condition is achieved by using 70 gsm HVS paper and drawing paper with a 52 training image database. The system can only carry out the process of recognition of one character, so it can be used as a reference translator of audio-based braille characters that can be heard by the visually impaired and the community. Keywords : image processing, braille, OCR, JST, text to speech Abstrak Indera penglihatan merupakan sumber informasi pada manusia. Sebagian manusia diciptakan dengan keterbatasan indera penglihatan. Tunanetra melakukan aktifitas membaca serta menulis menggunakan huruf Braille, yaitu sistem cetakan berupa kode terdiri dari enam titik dalam berbagai kombinasi yang ditonjolkan pada kertas sehingga dapat diraba. Untuk memudahkan tunanetra dan masyarakat dalam menikmati karya-karya yang dihasilkan oleh penyandang tunanetra dibuat sistem pembacaan naskah berkarakterkan Braille dengan mempelajari karakter braille terlebih dahulu dari masing-masing karakternya. Penelitian ini membuat sistem identifikasi huruf braille menjadi suara menggunakan computer vision. Metodenya, pembacaan naskah berkarakter Braille dengan mempelajari karakter braille. Pertama, scanner atau kamera berbasis Raspberry Pi mengcapture karakter braille. Kedua, sistem mengkonversi karakter Braille ke bentuk abjad dengan pengolahan citra Optical Character Recognition. Pengenalan pola karakter Braille teks tulisan menggunakan Jaringan Saraf Tiruan. Hasil penelitian pengujian huruf braille berupa teks abjad a sampai z, dan sinyal suara pengucapan abjad menggunakan sistem Text To Speech . Sistem konversi braille menjadi suara bekerja dengan baik, dengan akurasi rata-rata pengujian sistem yaitu 88.462%. Kondisi ini dicapai dengan menggunakan kertas HVS 70 gsm dan kertas gambar dengan database 52 citra latih. Sistem hanya dapat melakukan proses pengenalan pada satu karakter, sehingga dapat digunakan sebagai referensi penterjemah naskah karakter braille berbasis audio yang dapat didengarkan oleh tunanetra dan masyakat. Kata Kunci : image processing, braille, OCR, JST, text to speec

Aplikasi Identifikasi Huruf Braille Menggunakan Computer Vision Berbasis Raspberry Pi

Sense of vision is a source of information on humans. Some humans are created with limited sense of sight. The blind performs reading and writing activities using Braille letters, a printed code system consisting of six dots in various combinations that are highlighted on the paper so that they can be touched. To facilitate the visually impaired and the public in enjoying the works produced by blind people, a script reading system is characterized by Braille by studying the braille characters in advance of each character. This research makes a braille letter identification system into sound using computer vision. The method, the reading of Braille character scripts by studying braille characters. First, a scanner or Raspberry Pi-based camera captures braille characters. Second, the system converts Braille characters into alphabetical shapes by processing Optical Character Recognition images. Recognition of Braille character patterns in written text using Artificial Neural Networks. The results of research on braille testing are in the form of alphabetical texts a through z, and the sound signal of the pronunciation of the alphabet uses the Text To Speech system. Braille to sound conversion system works well, with an average accuracy of system testing of 88.462%. This condition is achieved by using 70 gsm HVS paper and drawing paper with a 52 training image database. The system can only carry out the process of recognition of one character, so it can be used as a reference translator of audio-based braille characters that can be heard by the visually impaired and the community.Keywords : image processing, braille, OCR, JST, text to speechAbstrakIndera penglihatan merupakan sumber informasi pada manusia. Sebagian manusia diciptakan dengan keterbatasan indera penglihatan. Tunanetra melakukan aktifitas membaca serta menulis menggunakan huruf Braille, yaitu sistem cetakan berupa kode terdiri dari enam titik dalam berbagai kombinasi yang ditonjolkan pada kertas sehingga dapat diraba. Untuk memudahkan tunanetra dan masyarakat dalam menikmati karya-karya yang dihasilkan oleh penyandang tunanetra dibuat sistem pembacaan naskah berkarakterkan Braille dengan mempelajari karakter braille terlebih dahulu dari masing-masing karakternya. Penelitian ini membuat sistem identifikasi huruf braille menjadi suara menggunakan computer vision. Metodenya, pembacaan naskah berkarakter Braille dengan mempelajari karakter braille. Pertama, scanner atau kamera berbasis Raspberry Pi mengcapture karakter braille. Kedua, sistem mengkonversi karakter Braille ke bentuk abjad dengan pengolahan citra Optical Character Recognition. Pengenalan pola karakter Braille teks tulisan menggunakan Jaringan Saraf  Tiruan. Hasil penelitian pengujian huruf braille berupa teks abjad a sampai z, dan sinyal suara pengucapan abjad menggunakan sistem Text  To Speech . Sistem konversi braille menjadi suara bekerja dengan baik, dengan akurasi rata-rata pengujian sistem yaitu 88.462%. Kondisi ini dicapai dengan menggunakan kertas HVS 70 gsm dan kertas gambar dengan database 52 citra latih. Sistem hanya dapat melakukan proses pengenalan pada satu karakter, sehingga dapat digunakan sebagai referensi penterjemah naskah karakter braille berbasis audio yang dapat didengarkan oleh tunanetra dan masyakat.Kata Kunci : image processing, braille, OCR, JST, text to speech

Working Effectively with People who are Blind or Visually Impaired

This brochure on peoples who are blind or visually impaired and The Americans with Disabilities Act (ADA) is one of a series on human resources practices and workplace accommodations for persons with disabilities edited by Susanne M. Bruyère, Ph.D., CRC, SPHR, Director, Program on Employment and Disability, School of Industrial and Labor Relations – Extension Division, Cornell University

Assistive Technology, Accommodations, and the Americans with Disabilities Act

This brochure on Assistive Technology, Accommodations, and the Americans with Disabilities Act (ADA) is one of a series on human resources practices and workplace accommodations for persons with disabilities edited by Susanne M. Bruyère, Ph.D., CRC, SPHR, Director, Program on Employment and Disability, School of Industrial and Labor Relations - Extension Division, Cornell University. Cornell University was funded in the early 1990’s by the U.S. Department of Education National Institute on Disability and Rehabilitation Research as a National Materials Development Project on the employment provisions (Title I) of the ADA (Grant #H133D10155). These updates, and the development of new brochures, have been funded by Cornell’s Program on Employment and Disability and the Pacific Disability and Business Technical Assistance Center