scholarly journals Smart Glass for Visually Challenged Peoples to Read the Books using Raspberry Pi

2021 ◽  
pp. 258-262
Author(s):  
Anitha D B ◽  
Jyothi T M ◽  
Pooja R ◽  
Sahana N
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Computer Software ◽  
Raspberry Pi ◽  
Text To Speech ◽  
Smart Glasses ◽  
Optical Character ◽  
Text Reading ◽  
Visually Challenged ◽  
Audio Output

The objective of this paper is to presents new design on assistive smart glasses for visually impaired. The objective is to assist in multiple daily tasks using the advantage of wearable design format. The proposed method is a camera based assistive text reading to help to blind in person in reading the text present on the text labels, printed notes and products in their own respective languages. It combines the concept of Optical Character Recognition (OCR), text to Speech Synthesizer (TTS) and translator in Raspberry pi. Optical character recognition (OCR) is the identification of printed characters using photoelectric devices and computer software. It converts images of typed, handwritten or printed text into machine encoded text from scanned document or from subtitle text superimposed on an image. Text-to-Speech conversion is a method that scans and reads any language letters and numbers that are in the image using OCR technique and then translates it into any desired language and at last it gives audio output of the translated text. The audio output is heard through the raspberry pi's audio jack using speakers or earphones.

scholarly journals Implementation of Optical Character Recognition Using Raspberry Pi for Visually Challenged Person

2018 ◽  
Vol 7 (3.34) ◽  
pp. 65 ◽  
Author(s):  
S Thiyagarajan ◽  
Dr G.Saravana Kumar ◽  
E Praveen Kumar ◽  
G Sakana
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Speech Synthesis ◽  
Native Speaker ◽  
Image Data ◽  
Raspberry Pi ◽  
Spoken Discourse ◽  
Optical Character ◽  
Digital Format ◽  
Visually Challenged

Blind people are unable to perform visual tasks. The majority of published printed works does not include Braille or audio versions, and digital versions are still a minority. In this project, the technology of optical character recognition (OCR) enables the recognition of texts from image data. The system is constituted by the raspberry pi, HD camera and Bluetooth headset. This technology has been widely used in scanned or photographed documents, converting them into electronic copies. The technology of speech synthesis (TTS) enables a text in digital format to be synthesized into human voice and played through an audio system. The objective of the TTS is the automatic conversion of sentences, without restrictions, into spoken discourse in a natural language, resembling the spoken form of the same text, by a native speaker of the language.  

scholarly journals A Smart Reader for Blind People

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1566-1568
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Raspberry Pi ◽  
Human Communication ◽  
Human Needs ◽  
Normal People ◽  
Optical Character ◽  
Visually Impaired People ◽  
Visually Challenged

This paper presents an intelligent bot for aiding the visually challenged people. Presently, 81% are visually impaired who live in the developing countries. Nowadays Human communication is mainly focused on text and speech. To read the text a human needs a vision. Survey conducted on several papers and systems provides hardware consisting of a camera interface with Raspberry Pi for processing the text. The camera captures text image of a handwritten or printed text. The raspberry pi makes use of Optical Character Recognition (OCR) software installed in it, to perform the conversion of an image to text and similarly text to speech conversion. The assistant is applicable for visually impaired people as well as for normal people in order to increase their level of comfort.

Smart Reader for Visually Challenged Using Optical Character Recognition and Text-To-Speech

2020 ◽  
pp. 205-208
Author(s):  
Sowmya R ◽  
Sushma S Jagtap ◽  
Gnanamoorthy Kasthuri
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Speech Synthesis ◽  
Read Aloud ◽  
Text To Speech ◽  
Digital Text ◽  
Optical Character ◽  
The People ◽  
Text To Speech Synthesis ◽  
Visually Challenged

Assistive technology uses assistive, adaptive and rehabilitative devices for people with disabilities. It’s assessed there are about 36 million people with visual impairment in the world and a further 216 million who lead life with moderate to severe visual impairments. Leveraging technology has helped the visually challenged in carrying out tasks on par with the people blessed with vision particularly in the activities of reading and writing. In the proposed work, an image scanning device attached to a microcontroller is designed. This device is designed in the form of hand gloves for ease of usage. The glove with the camera at the fingertip, when rolled over lines of text, scans the information and converts it into digital text with Optical Character Recognition (OCR). The converted digital text is finally read aloud using Text-to-speech synthesis. The results obtained were accurate and met the standards of operability.

scholarly journals Camera-Based Parking System Management Using Raspberry Pi

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Ahmad Zatnika Purwalaksana ◽  
Dewi Siburian ◽  
Immanuel Sianturi ◽  
Sabam Sianturi
Keyword(s):  
Data Storage ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Raspberry Pi ◽  
System Management ◽  
Data Recording ◽  
Optical Character ◽  
Vehicle Data ◽  
Parking System ◽  
One Time Password

Currently, there are still many use of manual parking systems, namely parking attendants provide instructions for vehicles to park. This is often considered inefficient because there is no data recording of vehicles that park, resulting in a low level of security and comfort for visitors and the parking system does not provide information about parking slots which can make it difficult for visitors to park vehicles. With this, the vehicle that wants to park often has difficulty when parking the vehicle. Through various problems that occur, the author develops a parking system that can provide information on the availability of parking slots in the parking area as well as data storage for vehicle number plates that do parking. In the parking system, the Raspberry Pi 3 Model B is used as the main controller, camera detection to obtain information in the form of characters from the vehicle number plate with the help of OCR (Optical Character Recognition), the use of OTP (One Time Password) code which can be used only once so as to increase security. on the parking system. Vehicle data in the form of number plates and also OTP code will be stored in the database and used when the vehicle will leave the parking area by matching the number plate data and OTP code of a vehicle to be able to leave the parking area. Through the development of the parking system, it is hoped that it will work well for vehicle drivers to find available parking locations and increase safety and comfort for drivers because of data storage in the form of vehicle number plates as vehicle identity and the use of OTP codes that can only be used once.

scholarly journals Development of Text to Speech Conversion System for Low Vision and Blind People

2020 ◽  
Vol 9 (4) ◽  
pp. 2154-2158
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Low Vision ◽  
World Health ◽  
Thought Process ◽  
Speech Output ◽  
Optical Character ◽  
Content Recognition ◽  
Visually Challenged ◽  
Health Organization

Around the world 285 million individuals are found to be visually challenged out of 7.4 billion populations found in a survey made by World Health Organization. These people face many problems but the major problem is reading. It is observed that they cannot read the text which is not written in braille. In the thought process of supporting them, here is a framework proposed for the visually challenged people which can perform content recognition and produce voice yield. This can assist the visually challenged people with reading any printed content and convey in speech output. A camera is utilized to capture the content from the printed content and the captured picture experiences progression of picture pre-preprocessing steps to get the content of the picture and expels the background. Characters are identified utilizing Tesseract-Optical Character recognition (OCR). The identified script is then changed into voice, utilizing open source speech synthesizer (TTS). Finally, the speech output is heard by the earphones.

scholarly journals Identifikasi Plat Nomor Kendaraan Dengan Metode Optical Character Recognition Menggunakan Raspberry Pi

2020 ◽  
Vol 7 (2) ◽  
pp. 116-125
Author(s):  
Winarno Sugeng ◽  
Rio Korio Utoro ◽  
Mochamad Tegar Prabowo
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Raspberry Pi ◽  
Error Handling ◽  
Optical Character

Plat Nomor Kendaraan merupakan identitas bagi setiap kendaraan bermotor yang terdaftar oleh pemerintah Indonesia. Proses identifikasi plat nomor diawali dengan pembambilan gambar kendaraan dengan kamera. Gambar akan di resize untuk menyamakan ukuran citra dan crop untuk memisahkan antara plat nomor dengan bagian kendaraan lainnya menggunakan algoritma Perspective Transform, setelah itu di crop kembali untuk memisahkan antara kode wilayah, kode registrasi dan kode seri wilayah, lalu setiap karakter akan dikenali menggunakan metode Optical Character Recognition (OCR) berdasarkan citra karakter hasil crop. Terdapat proses character error handling untuk meningkatkan tingkat akurasi identifikasi pada karakter plat nomor. Plat nomor Indonesia yang diujikan terbagi menjadi 4 kategori yaitu Plat Standar Mobil, Plat Kustom Mobil, Plat Tidak Standar dan Plat Motor. Resolusi kamera terbaik menggunakan resolusi 1280x720 piksel dan menghasilkan rata-rata waktu uji 6,51 detik. Persentase kebenaran identifikasi karakter terbesar untuk plat standar sebesar 100% pada nilai lux 20~39 dan nilai lux 70~99, sedangkan untuk plat nomor kustom persentase kebenaran identifikasi karakter terbesar sebesar 58% pada nilai lux 90~140. Sedangkan untuk plat tidak standar tidak ada persentase kebenaran identifikasi karakter terbesar menghasilkan persentase 0% pada semua nilai lux yang diujikan. Untuk plat nomor motor persentase kebenaran identifikasi karakter terbesar sebesar 8% pada nilai lux 150~199. Sehingga dapat ditarik kesimpulan bahwa plat nomor standar menjadi rekomendasi yang tepat bagi setiap kendaraan bermotor yang ada di Indonesia.

scholarly journals Rancang Bangun Palang Otomatis Dengan Pengenalan Plat Kendaraan Menggunakan OpenALPR

2020 ◽  
Vol 5 (4) ◽  
pp. 36
Author(s):  
Rahmat Darmawan ◽  
Ahmad Taqwa ◽  
Jon Endri
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Raspberry Pi ◽  
Optical Character

Dikarenakan meningkatnya penggunaan lahan parkir dan keterbatasan lahan, maka seringkali lahan parkir tidak digunakan secara tepat. Namun masalah tersebut dapat diatasi dengan cara mengimplementasikan sistem palang otomatis dengan pendeteksian plat nomor kendaraan berbasis raspberry pi. Proses pengenalan plat nomor kendaraan dilakukan dengan metode optical character recognition (ocr). Hasil pada tugas akhir ini akan menampilkan plat yang telah terdeteksi dan merespon ke output yang disediakan.

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