S. Venkateswarlu ¹, D. B. K. Kamesh ¹, J. K. R. Sastry ², Radhika Rani ¹

Affiliations
1 Department of CSE, K L University, Vaddeswarm, Guntur – 522502, Andhra Pradesh, IN
2 Department of ECM, K L University, Vaddeswarm, Guntur – 522502, Andhra Pradesh, IN

Abstract

The present paper has introduced an innovative, efficient and real-time cost beneficial technique that enables user to hear the contents of text images instead of reading through them. It combines the concept of Optical Character Recognition (OCR) and Text to Speech Synthesizer (TTS) in Raspberry pi. This kind of system helps visually impaired people to interact with computers effectively through vocal interface. Text Extraction from color images is a challenging task in computer vision. Text-to-Speech conversion is a method that scans and reads English alphabets and numbers that are in the image using OCR technique and changing it to voices. This paper describes the design, implementation and experimental results of the device. This device consists of two modules, image processing module and voice processing module. The device was developed based on Raspberry Pi v2 with 900 MHz processor speed.

Keywords

Image Processing, OCR, Text Extraction, Text-to-speech, Voice Processing.

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D. B. K. Kamesh ¹, K. Rama Krishna ¹, J. K. R. Sastry ¹

Affiliations
1 Department of Electronics and Computer Engineering, K L University, Vaddeswaram - 522502, Guntur District, Andhra Pradesh, IN

Abstract

Background/Objectives: The main objective of this paper is to provide a novel method of identification and authentication of a user through a process of enhancing the password level protection to provide authorised use of the resources hosted on the WEB. Methods/Statistical Analysis: The authentication process that uses mind metrics has been implemented within ARM7 Micro controller which is made to act as central server. The process of authentication and the implementation of the same have been explained through an architectural diagram. Software which has been written using KEIL IDE is burnt into a Micro controller and the implementation of an authentication process has been implemented through a GSM device connected to a Micro controller. Findings: A novel approach that considers a Personnel secret token known as mind metrics has been presented. The server sends across the mind metrics to the user after completing the identification phase and the user from then uses password and mind metrics to carry secured communication between the user and the server. Applications/Improvements: The method has been implemented both as a software and hardware solution. The software solution has been implemented within a GSM application for enabling text message notification.

Keywords

ARM, Authentication, KEIL IDE, Key Loggers, Login systems, Mind Metrics.

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S. Nazma ¹, D. B. K. Kamesh ¹, J. K. R. Sastry ¹, S. Venkateswarlu ¹

Affiliations
1 Department of Electronics and Computer Engineering, KL University, Vaddeswaram - 522 502, Guntur District, Andhra Pradesh, IN

Abstract

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.

Keywords

Camera based Detection for Blind Persons, Currency Detection, Raspberry Pi Board, Text to Speech Conversion.

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