Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Android Based Currency Recognition System for Blind

Author : Nayana Susan Jose 1 Shermin Siby 2 Juby Mathew 3 Mrudula Das 4

Date of Publication :7th June 2015

Abstract: There are around 285 Million people who are visually impaired worldwide[1]. One of the greatest difficulty faced by a blind person is to know the value of the currency that he or she has. It becomes a great difficulty for them to exchange money during purchases and they may get cheated in many instances. This paper is mainly built to support them and make them easier to get used to the currencies. Here, we propose an android based application for recognizing currencies of different countries and also their denominations mainly for visually impaired people. Image processing techniques like feature extraction and matching are used to identify currencies. This application runs on a low end smartphone. We give an audio message as the input to start the app and to capture the image. Then the image is captured and is compared with the test image. If the features of both the images are spatially consistent, then an audio output is given to the user about the denomination of the currency and to which country it belongs to. Otherwise, an error message is given as output.

Reference :

    1. Faiz M. Hasanuzzaman, Xiaodong Yang, and YingLi Tian, Senior Member, IEEE. Robust and Effective Component-Based Banknote Recognition for the Blind
    2. JunfangGuo, Yanyun Zhao, AnniCai Multimedia Communication and Pattern Recognition Labs, Beijing. A reliable method for paper currency recognition based on lbp
    3. KuldeepVerma, Bhupesh Kumar Singh, AnupamAgarwal Institute of technology, Nirma university.Indian Currency Recognition based on Texture Analysis
    4. Yuan Feng Department of Computer science Nanjing University,China.Extraction of serial number on Bank notes
    5. Jarrett Chambers Auckland University,Newzealand. An empirical approach for Digital currency forensics
    6. 2013 5th International conference on intelligent networking and collaborative systems Shanghai,Finance university China. A real-time template generation algorithm to identify RMB crest number

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