Braille-Lippi Numbers and Characters Detection and Announcement System for Blind Children Using KSK Approach: AI-Driven Decision-Making Approach

Abstract

In order to develop a Braille-Lippi character recognition system, a number of different strategies and procedures have been utilized, with the KSK Approach being the primary tool utilized. When doing analysis, the KSK Approach makes use of DT, ANN, and K-NN classifiers. In comparison to other computational methods, the KSK Approach is superior in terms of its efficiency and reliability when it comes to recognising Braille characters. The page contains the results of testing and system development, as well as the technique, design, and architecture of the Braille character recognition system, which has a 99% accuracy rate. This also makes it possible to use the Voicing System, which is responsible for announcing the letter that has been recognized.