A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classification
Detecting authentic and quality banknotes presents a significant challenge, particularly for individuals with low vision or visual impairments. Extensive research has been dedicated to achieving accurate banknote detection. It is crucial for clean banknotes to be readily detectable and accepted in d...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235234092300776X |
| _version_ | 1797429964647170048 |
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| author | Vidula Meshram Vishal Meshram Kailas Patil Yogesh Suryawanshi Prawit Chumchu |
| author_facet | Vidula Meshram Vishal Meshram Kailas Patil Yogesh Suryawanshi Prawit Chumchu |
| author_sort | Vidula Meshram |
| collection | DOAJ |
| description | Detecting authentic and quality banknotes presents a significant challenge, particularly for individuals with low vision or visual impairments. Extensive research has been dedicated to achieving accurate banknote detection. It is crucial for clean banknotes to be readily detectable and accepted in daily transactions. However, existing Indian currency datasets suffer from limitations, including insufficient size, a lack of datasets on damaged/spoiled banknotes, and the unavailability of publicly accessible datasets featuring spoiled, torn, or altered banknotes. Recognizing the vital importance of a spoiled banknote dataset for the benefit of low vision and visually impaired individuals, we introduce a comprehensive dataset of spoiled banknotes comprising 5125 Indian currency notes. This dataset encompasses both old and new denominations of 10, 20, 50, and 100 Rupees, aiming to significantly enhance the accessibility and accuracy of banknote detection systems. By making this dataset openly accessible to the researchers, we aim to promote research and development of solutions for detection of spoiled banknote. |
| first_indexed | 2024-03-09T09:21:53Z |
| format | Article |
| id | doaj.art-25919bb105c24e2582710507aeaba932 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-03-09T09:21:53Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-25919bb105c24e2582710507aeaba9322023-12-02T07:00:06ZengElsevierData in Brief2352-34092023-12-0151109699A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classificationVidula Meshram0Vishal Meshram1Kailas Patil2Yogesh Suryawanshi3Prawit Chumchu4Vishwakarma Institute of Information Technology, Pune, PIN-411038, IndiaVishwakarma Institute of Information Technology, Pune, PIN-411038, IndiaVishwakarma University, Pune, PIN-411038, India; Corresponding authors.Vishwakarma University, Pune, PIN-411038, IndiaKasetsart University, Sriracha, Thailand; Corresponding authors.Detecting authentic and quality banknotes presents a significant challenge, particularly for individuals with low vision or visual impairments. Extensive research has been dedicated to achieving accurate banknote detection. It is crucial for clean banknotes to be readily detectable and accepted in daily transactions. However, existing Indian currency datasets suffer from limitations, including insufficient size, a lack of datasets on damaged/spoiled banknotes, and the unavailability of publicly accessible datasets featuring spoiled, torn, or altered banknotes. Recognizing the vital importance of a spoiled banknote dataset for the benefit of low vision and visually impaired individuals, we introduce a comprehensive dataset of spoiled banknotes comprising 5125 Indian currency notes. This dataset encompasses both old and new denominations of 10, 20, 50, and 100 Rupees, aiming to significantly enhance the accessibility and accuracy of banknote detection systems. By making this dataset openly accessible to the researchers, we aim to promote research and development of solutions for detection of spoiled banknote.http://www.sciencedirect.com/science/article/pii/S235234092300776XClassificationCurrency recognitionDamaged banknotesIndian currencySpoilt banknotes |
| spellingShingle | Vidula Meshram Vishal Meshram Kailas Patil Yogesh Suryawanshi Prawit Chumchu A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classification Data in Brief Classification Currency recognition Damaged banknotes Indian currency Spoilt banknotes |
| title | A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classification |
| title_full | A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classification |
| title_fullStr | A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classification |
| title_full_unstemmed | A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classification |
| title_short | A comprehensive dataset of damaged banknotes in Indian currency (Rupees) for analysis and classification |
| title_sort | comprehensive dataset of damaged banknotes in indian currency rupees for analysis and classification |
| topic | Classification Currency recognition Damaged banknotes Indian currency Spoilt banknotes |
| url | http://www.sciencedirect.com/science/article/pii/S235234092300776X |
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