Currency Recognization for visually impaired People using Tensorflow

Authors

  • Mr. Nikhil Brahmapurikar B.E.[CSE] Student, Tulsiramji Gaikwad-Patil College of Engineering & Technology, Nagpur, India
  • Ms. Renuka Fate B.E.[CSE] Student, Tulsiramji Gaikwad-Patil College of Engineering & Technology, Nagpur, India
  • Ms. Naina Bhoskar B.E.[CSE] Student, Tulsiramji Gaikwad-Patil College of Engineering & Technology, Nagpur, India
  • Ms. Gayatri Rakshak B.E.[CSE] Student, Tulsiramji Gaikwad-Patil College of Engineering & Technology, Nagpur, India
  • Mr. Jiwan Dehankar Assistant Professor, Tulsiramji Gaikwad-Patil College of Engineering & Technology, Nagpur, India

Keywords:

Image processing, Data analysis, aspect ratio, curruency regontion

Abstract

In this research, we present an image processing-based system for automatic money recognition. The proposed approach can be used to identify a banknote's country of origin, as well as its denomination and value.Only paper currencies have been taken into account. This method works by first identifying the country of origin using predetermined areas of interest, and then extracting the denomination value from the note's size, colour, or text. Picture preprocessing, image analysis, and image recognition are all part of the detecting system. The descriptor of an individual input scene is matched with multiple training photos of the same category to improve the determination of money recognition.The currency is then recognised with greater confidence after assessing their matching result. We've turned the technology into a smartphone application for real-time recognition.

References

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Published

18-04-2022

How to Cite

Mr. Nikhil Brahmapurikar, Ms. Renuka Fate, Ms. Naina Bhoskar, Ms. Gayatri Rakshak, & Mr. Jiwan Dehankar. (2022). Currency Recognization for visually impaired People using Tensorflow. International Journal for Research Publication and Seminar, 13(3), 43–46. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/523

Issue

Vol. 13 No. 3 (2022): Volume 13 | Issue 3 | 2022 (NSCIT)

Section

Original Research Article

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