Phonic Eye for the Visually Impaired
Meenatchi KV1, Mahima S2, Poornima T3, P Kumar4
1Meenatchi KV, Student, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai (Tamil Nadu), India.
2Mahima S, Student, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai (Tamil Nadu), India.
3PoornimaT, Student, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai (Tamil Nadu), India.
4Dr. P Kumar, M.E, Ph.D. Professor, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai (Tamil Nadu), India.
Manuscript received on 29 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 22 June 2019 | PP: 546-549 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C11170283S19/19©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: Visual disability is a physical abnormality that deters a person from performing day to day activities due to the lack of awareness about the surroundings. The greatest challenge faced by the visually impaired people is to identify the things around them and they need to be dependent on other people when they require usage of a particular product or identifying any obstacle on their path. Though there are numerous applications built for the visually impaired, the goal of the proposed solution is to create an interactive mobile application based on the object detection technology to report the user about the vicinity. This mobile application serves as an effective tool in enhancing the experience of the user by capturing the image of the scene in the environment and identifying the objects in the frame with the application of Convolutional Neural Networks based on faster Region based Convolutional Neural Network model and the results are delivered to the user in the form of speech signals thereby enabling the users to be self-reliant and phonetically observe the locale.
Keywords: Tensor Flow, Faster_Rcnn, Flask, TF Serving, TTS, Blind, Visually Impaired, Object Detection.
Scope of the Article: Application Specific ICs (ASICs)