Pakistani Currency Recognition to Assist Blind Person Based on Convolutional Neural Network

Journal of Computer Science and Technology Studies

View Publication Info
 
 
Field Value
 
Title Pakistani Currency Recognition to Assist Blind Person Based on Convolutional Neural Network
 
Creator Imad, Muhammad
Ullah , Farhat
Abul Hassan, Muhammad
Naimullah
 
Subject Pakistani Currency, CNN, Object Recognition, Support Vector Machine, Visually Impaired People.
 
Description A visually impaired person faces many difficulties in their daily life, such as having trouble finding their ways, recognize the person and objects. One of the crucial problems is to recognize the currencies for a blind or visually impaired person. In this research article, we have proposed a system to recognize a Pakistani currency for a blind or visually impaired person based on Convolutional Neural Network (CNN) and Support Vector Machine (SVM). In the proposed system, seven different Pakistani paper currency notes (Rs.10, 20, 50, 100,500, 1000 and 5000) are used for training and testing. Experimental results show that the proposed system can recognize seven notes of Pakistan's Currency (Rs. 10, 20, 50, 100, 500, 1000, 5000) successfully with an accuracy of 96.85%.
 
Publisher Al-Kindi Center for Research and Development
 
Date 2020-10-06
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://al-kindipublisher.com/index.php/jcsts/article/view/529
 
Source Journal of Computer Science and Technology Studies; Vol. 2 No. 2 (2020): Journal of Computer Science and Technology Studies; 12-19
2709-104X
 
Language eng
 
Relation https://al-kindipublisher.com/index.php/jcsts/article/view/529/488
 
Rights Copyright (c) 2020 Journal of Computer Science and Technology Studies
 

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