1. Deep Learning Approach to detect
Currency by using Voiceover
Presented By-
53 Mukti Kalsekar
59 Shubhangi Shirke
Guided By:
Prof. Amrapali Patil
Usha Mittal Institute of Technology
June 07,2021

2. Content
● Introduction
● Tools Used
● Idea behind this project
● Algorithm
● Methodology
● Output and result
● Dataset Used
● Literature Survey
● Diagrams
● Conclusion
● References

3. Introduction
● For blind people it's not easy to recognize the paper currencies due to the similarity
of paper texture and size between the different categories.
● Hence, the role of technology is to develop a solution to resolve this crisis to make
blind people feel safe and confident in the financial dealings.
● This Application can be used in smartphone with voice commands.
● This application is user friendly and convenient to use

4. Tools Used
● Android Studio
● Teachable Machine Platform Provided By Google
● Tensorflow Lite
● Dataset

5. Idea behind this project
● Making Blind people independent in daily financial dealings
● Feel safe and Confident
● Easy to use

6. Algorithm
1. Algorithm used in project is CNN (Convolution Neural Network)
2. These layers performs learning operations on the given data.
● Convolution
● Pooling
● Denser layer
Input
Layer
Convolution
Layer
Pooling
Layer
Denser
Layer
Output
Layer

7. ● Train the model using dataset
● Export the model in android studio
● By using this model, it will convert the text into voice
Methodology

8. Output

9. Result
● It will capture the currency
● The currency is compare with the dataset
● The dataset contains different classes which are created into model
● After comparing it give result on the basis of data similarity and from which we can
detect the currency
● It also convert the text into voice, so we can understand how much the currency is.

10. Dataset Used
Vishal mane ,Indian Currency Note images dataset 2020,Dataset updated 7 months
ago on kaggle
website.
● https://www.kaggle.com/vishalmane109/indian-currency-note-images-dataset-2020
Shobhit Shrivastava , Indian currency notes,updated a year ago on kaggle website.
● https://www.kaggle.com/shobhit18th/indian-currency-notes
Gurav Rajesh Sahani,Indian currency notes classifier,updated 10 months ago on kaggle
website.
● https://www.kaggle.com/gauravsahani/indian-currency-notes-classifier

11. Literature Survey :
❏ During the survey we find that they used :
● In first research paper they used Image processing techniques ,Image
Foreground segmentation , Histogram enhancement ,ROI
● In Second research paper they used Machine Learning approach in assistive
technology with voice assistant.
● In Third research paper they used Image processing, image analysis, image
recognition ,ORB, open cv

12. Diagrams :
State Diagram
Flow chart

13. Conclusion :
● The application developed is user friendly and applicable in real time.
● This android application can be installed in a smartphone that allows
visually impaired people to use it easily and conveniently.

14. Reference
● Noura A. Semary, Sondos M. Fadl, Magda S. Essa, Ahmed F. Gad
"Currency Recognition System for Visually Impaired Egyptian Banknote
as a Study Case", 2015 ,5th international conference.
https://ieeexplore.ieee.org/document/7426896
● Sin-Chun Ng,Chok-Pang Kwok,Sin-Hang Chung,Yuen-Yan
Leung,Hoi-Shan Pang "An Intelligent Banknote Recognition System by using Machine
Learning with Assistive Technology for Visually Impaired People",September 9-15,
2020 10th International Conference on Information Science and Technology Bath,
United Kingdom
https://ieeexplore.ieee.org/document/9202087
● Md. Ferdousur Rahman Sarker, Md. Israfil Mahmud Raju, Ahmed Marouf,
Rubaiya Hafiz4, Syed Akhter Hossain “ Real-time Bangladeshi Currency
Detection System for Visually Impaired Person” 27-28,September,2019
International Conference on Bangla Speech and Language Processing (ICBSLP)
https://ieeexplore.ieee.org/document/9084039