Language Translation on Intelligent Navigation System using Image Processing

Abstract

Visitors traveling to different countries around the world often find it hard to understand and communicate in local languages, because they don't understand it. They can't read the words written on the navigational boards or banners at these new locations. Text detection, extraction, and translation system must, therefore, be built to identify and recognize the text found on the navigation boards. This system proposes and implements a three-stage process that involves detection, extraction, and translation using the concepts of Convolutional Neural Network (CNN) and Long Short Term Memory networks or simply “LSTMs”. The framework has been designed to take into account the need to create a desktop application that extracts the text from images based on traffic navigation boards and then translates it further into a user-understandable language. In this way, the user can grasp the unfamiliar language and roam freely in the unfamiliar terrains.