Abstract
Advanced technology has played an important role in the circulation of the banknote counterfeit and currency value recognition. This study proposes an approach for the currency recognition based on the fundamental image processing and deep learning for the extraction characteristics and recognition of currency values. The large capacity of traditional techniques was proposed for currency recognition based on infrared spectrometer and chemometrics using special devices. This paper presents a recognition method to detect face values from currency paper and. The proposed method can recognize some kinds of currency values and national currencies. The study investigated and proposed the deep neural network, which reaches appropriate accuracy rate and reduces consumption time. In order to improve accuracy of recognition model, data augmentation techniques are also investigated for training data preprocessing. The experimental results show that the proposed approach is applicable to the practical applications.
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Trinh, HC., Vo, HT., Pham, VH., Nath, B., Hoang, VD. (2020). Currency Recognition Based on Deep Feature Selection and Classification. In: Sitek, P., Pietranik, M., Krótkiewicz, M., Srinilta, C. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Communications in Computer and Information Science, vol 1178. Springer, Singapore. https://doi.org/10.1007/978-981-15-3380-8_24
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DOI: https://doi.org/10.1007/978-981-15-3380-8_24
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