Annotated Peruvian banknote dataset for currency recognition and classification.

Autor:	Caytuiro-Silva NE; Universidad Católica de Santa María, Arequipa Peru., Peña-Alejandro JM; Universidad Católica de Santa María, Arequipa Peru., Castro-Gutierrez EG; Universidad Católica de Santa María, Arequipa Peru., Sulla-Torres J; Universidad Católica de Santa María, Arequipa Peru., Maraza-Quispe B; Universidad Nacional de San Agustín de Arequipa, Arequipa Peru.
Jazyk:	angličtina
Zdroj:	Data in brief [Data Brief] 2023 Oct 24; Vol. 51, pp. 109715. Date of Electronic Publication: 2023 Oct 24 (Print Publication: 2023).
DOI:	10.1016/j.dib.2023.109715
Abstrakt:	The real-time detection of multinational banknotes remains an ongoing research challenge within the academic community. Numerous studies have been conducted to address the need for rapid and accurate banknote recognition, counterfeit detection, and identification of damaged banknotes [1], [2], [3]. State-of-the-art techniques, such as machine learning (ML) and deep learning (DL), have supplanted traditional digital image processing methods in banknote recognition and classification. However, the success of ML or DL projects critically hinges on the size and comprehensiveness of the datasets employed. Existing datasets suffer from several limitations. Firstly, there is a notable absence of a Peruvian banknote dataset suitable for training ML or DL models. Second, the lack of annotated data with specific labels and metadata for Peruvian currency hinders the development of effective supervised learning models for banknote recognition and classification. Lastly, datasets from different regions may not align with the unique characteristics, design, and security features of Peruvian banknotes, limiting the accuracy and applicability of models in a Peruvian context [4] To address these limitations, we have meticulously curated a comprehensive dataset comprising a total of 9,315 images of Peruvian banknotes, encompassing both old and new denominations from 2011 (old) and 2019 (new) [5]. The Peruvian banknote dataset includes denominations of 10, 20, 50, and 100 Peruvian soles. Importantly, as indicated by [5], both the 2011 and 2019 families of banknotes are currently in circulation, further enhancing the dataset's relevance for real-world applications in currency recognition and verification. This dataset serves as a vital resource for addressing the challenges in real-time multinational banknote detection. By offering a comprehensive collection of images of Peruvian banknotes, both old and new, this dataset fills a critical gap in the field of banknote recognition. Researchers can utilize it to train and evaluate advanced machine learning and deep learning models, ultimately enhancing the accuracy of banknote processing systems. Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (© 2023 The Author(s).)
Databáze:	MEDLINE
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