Camera based Text to Speech Conversion, Obstacle and Currency Detection for Blind Persons

Background/Objectives: The main object of this paper is to present an innovated system that can help the blind for handling currency. Methods/Statistical Analysis: Many image processing techniques have been used to scan the currency, remove the noise, mark the region of interest and convert the image into text and then to sound which can be heard by the blind. The entire system is implemented by using Raspberry Pi Micro controller based system. In the proto type model an IPR sensor is used instead of camera for sensing the object. Findings: In this paper a novel method has been presented using which one can recognize the object, mark the interesting region within the object, scan the text and convert the scanned text into binary characters through optical recognition. A second method has been presented using which the noise present in the scanned image is eliminated before characters are recognized. A third method that can be used to convert the recognised characters into e-speech through pattern matching has also be presented. Applications: An embedded system has been developed based on ARM technology which helps the blind persons to read the currency notes. All the methods presented in this paper have been implemented within an embedded application. The embedded board has been tested with different currency notes and the speech in English has been generated that identify the value of the currency. Further work can be done to generate the speech in different other both National and International Languages.