Efficient currency recognition and value detection system using image processing
Computer Science and Engineering with Specialization in Artificial Intelligence and Machine Learning, Srm Institue of Science and Technology, Chennai, Tamil Nadu, India.
Research Article
World Journal of Advanced Research and Reviews, 2024, 22(01), 241–255
Publication history:
Received on 19 February 2024; revised on 28 March 2024; accepted on 30 March 2024
Abstract:
In recent years, there has been a growing demand for automated currency recognition and value detection systems to streamline the processes of cash handling and financial transactions. Image processing techniques have emerged as a promising approach to automate these tasks. This paperwork presents an efficient currency recognition and value detection system based on image processing techniques. The proposed system aims to automate the currency recognition and value detection process, which is an essential task in many financial and retail applications. The system consists of several stages: image acquisition, image pre-processing, feature extraction, image augmentation, and classification. The system uses several image processing algorithms, including data augmentation to enhance the quality of the input images and extract the relevant features. These tasks involve identifying the denomination of a bank note or coin and determining its value. The experiments' results demonstrate the proposed system's effectiveness in real- world scenarios, which can significantly reduce the time and effort required for currency recognition and value detection. In conclusion, the proposed system achieves high accuracy and robustness in recognizing different currencies, including bank notes and coins, under various lighting conditions and orientations. The system's performance can significantly reduce the time and effort required for currency recognition and value detection, making it suitable for use in financial and retail applications. Future work will focus on improving the system's performance in more challenging scenarios, such as handling damaged or counterfeit currency.
Keywords:
Currency recognition; Currency value detection; Image processing; Image acquisition; Accuracy; Financial and Retail applications; Image augmentation
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0