Improve accessibility for Low Vision and Blind people using Machine
  Learning and Computer Vision
Jasur Shukurov
With the ever-growing expansion of mobile technology worldwide, there is an
increasing need for accommodation for those who are disabled. This project
explores how machine learning and computer vision could be utilized to improve
accessibility for people with visual impairments. There have been many attempts
to develop various software that would improve accessibility in the day-to-day
lives of blind people. However, applications on the market have low accuracy
and only provide audio feedback. This project will concentrate on building a
mobile application that helps blind people to orient in space by receiving
audio and haptic feedback, e.g. vibrations, about their surroundings in
real-time. The mobile application will have 3 main features. The initial
feature is scanning text from the camera and reading it to a user. This feature
can be used on paper with text, in the environment, and on road signs. The
second feature is detecting objects around the user, and providing audio
feedback about those objects. It also includes providing the description of the
objects and their location, and giving haptic feedback if the user is too close
to an object. The last feature is currency detection which provides a total
amount of currency value to the user via the camera.