Design and Implementation of Assistive Aid for Blind and Visually Impaired Users Using Raspberry Pi 3 Arm11 (Bcm2837)
M. Anto Bennet1, T. V. Pradhisha2, E. Vedhavalli3, B. Sesha Ramya4, D. Bhavani5
1M. Anto Bennet, Professor, Department of Electronics and Communication Engineering, Vel Tech, Chennai (Tamil Nadu), India.
2T. V. Pradhisha, UG Student, Department of Electronics and Communication Engineering, Vel Tech, Chennai (Tamil Nadu), India.
3E. Vedhavalli, UG Student, Department of Electronics and Communication Engineering, Vel Tech, Chennai (Tamil Nadu), India.
4B. Sesha Ramya, UG Student, Department of Electronics and Communication Engineering, Vel Tech, Chennai (Tamil Nadu), India.
5D. Bhavani, UG Student, Department of Electronics and Communication Engineering, Vel Tech, Chennai (Tamil Nadu), India.
Manuscript received on 23 April 2019 | Revised Manuscript received on 02 May 2019 | Manuscript Published on 07 May 2019 | PP: 145-148 | Volume-7 Issue-6S3 April 2019 | Retrieval Number: F1028376S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, we proposed an assistive aid for the visually impaired people. This will act as an identification and detection system which helps them to perform difficult tasks like reading, write and walk without help by means of sound commands. This paper carries a sequential operation of object and text recognition, currency denomination with fake note detection, obstacle detection and reading newspapers as well as books. Here the process is carried out in Raspberry pi ARM11 (BCM2837). In this processor, the text recognition and identification systems are integrated. The OCR (Optical Character Recognition) is used for converting the captured image into text and conveys to the blind people with the help of voice signals through Espeak engine. The currency notes with multiple denominations as well as fake note indication are detected using SURF algorithm. This integrated module helps the blind people to live their life independently without the help of others.
Keywords: ARM 11(BCM 2837), OCR(Optical Character Recognition), Espeak.
Scope of the Article: Low-power design