Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms
Banknote recognition means classifying the currency (coin and paper) to the correct class. In this paper, we developed a dataset for Jordanian currency. After that we applied automatic mobile recognition system using a smartphone on the dataset using scale-invariant feature transform (SIFT) algorith...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2017-10-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157816300416 |
| _version_ | 1817983397012701184 |
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| author | Iyad Abu Doush Sahar AL-Btoush |
| author_facet | Iyad Abu Doush Sahar AL-Btoush |
| author_sort | Iyad Abu Doush |
| collection | DOAJ |
| description | Banknote recognition means classifying the currency (coin and paper) to the correct class. In this paper, we developed a dataset for Jordanian currency. After that we applied automatic mobile recognition system using a smartphone on the dataset using scale-invariant feature transform (SIFT) algorithm. This is the first attempt, to the best of the authors knowledge, to recognize both coins and paper banknotes on a smartphone using SIFT algorithm. SIFT has been developed to be the most robust and efficient local invariant feature descriptor. Color provides significant information and important values in the object description process and matching tasks. Many objects cannot be classified correctly without their color features. We compared between two approaches colored local invariant feature descriptor (color SIFT approach) and gray image local invariant feature descriptor (gray SIFT approach). The evaluation results show that the color SIFT approach outperforms the gray SIFT approach in terms of processing time and accuracy. |
| first_indexed | 2024-04-13T23:32:37Z |
| format | Article |
| id | doaj.art-91fa2299ad5240cb9fb2ba6c11d6611b |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-13T23:32:37Z |
| publishDate | 2017-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-91fa2299ad5240cb9fb2ba6c11d6611b2022-12-22T02:24:51ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782017-10-0129448449210.1016/j.jksuci.2016.06.003Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithmsIyad Abu DoushSahar AL-BtoushBanknote recognition means classifying the currency (coin and paper) to the correct class. In this paper, we developed a dataset for Jordanian currency. After that we applied automatic mobile recognition system using a smartphone on the dataset using scale-invariant feature transform (SIFT) algorithm. This is the first attempt, to the best of the authors knowledge, to recognize both coins and paper banknotes on a smartphone using SIFT algorithm. SIFT has been developed to be the most robust and efficient local invariant feature descriptor. Color provides significant information and important values in the object description process and matching tasks. Many objects cannot be classified correctly without their color features. We compared between two approaches colored local invariant feature descriptor (color SIFT approach) and gray image local invariant feature descriptor (gray SIFT approach). The evaluation results show that the color SIFT approach outperforms the gray SIFT approach in terms of processing time and accuracy.http://www.sciencedirect.com/science/article/pii/S1319157816300416Currency recognitionSIFT algorithmMobile currency recognition |
| spellingShingle | Iyad Abu Doush Sahar AL-Btoush Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms Journal of King Saud University: Computer and Information Sciences Currency recognition SIFT algorithm Mobile currency recognition |
| title | Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms |
| title_full | Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms |
| title_fullStr | Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms |
| title_full_unstemmed | Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms |
| title_short | Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms |
| title_sort | currency recognition using a smartphone comparison between color sift and gray scale sift algorithms |
| topic | Currency recognition SIFT algorithm Mobile currency recognition |
| url | http://www.sciencedirect.com/science/article/pii/S1319157816300416 |
| work_keys_str_mv | AT iyadabudoush currencyrecognitionusingasmartphonecomparisonbetweencolorsiftandgrayscalesiftalgorithms AT saharalbtoush currencyrecognitionusingasmartphonecomparisonbetweencolorsiftandgrayscalesiftalgorithms |