STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Artificial Intelligence Research & Advances

Oculight: AI Based System for Visual Assistance to Blind and Visually Impaired People

  1. Shreya Tandale
  2. Shyam Pawar
  3. Sanjivani Singh
  4. Sukriti Singh
  5. Prajakta Jadhav

Abstract

This research introduces a new captioning model that utilizes both image and caption models to produce textual descriptions of images. By combining a convolutional neural network (CNN) and a long short-term memory (LSTM) recurrent neural network (RNN), this deep learning architecture offers a promising solution for improving the quality of life and independence of blind people through AIbased systems. The system's implementation on an Android device ensures that it is highly accessible and user-friendly, while the integration of text-to-speech technology further enhances its potential for improving human-computer interaction. The CNN is responsible for extracting meaningful features from input images, which the RNN then uses to generate textual descriptions. This research highlights the potential for future development to expand the system's capabilities to support a wider range of visual tasks and environments and improve the efficiency and accuracy of the model. With further refinement, this technology could have a profound impact on the lives of blind people, improving their overall well-being and sense of independence.

Keywords

Support