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Journal of Engineering and Applied Sciences

ISSN: Online 1818-7803
ISSN: Print 1816-949x
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Design of Foreign Currency Recognition Application using Scale Invariant Feature Transform (SIFT) Method based on Android (Case Study: Singapore Dollar)

Mohammad Rizky Adhiguna, Budhi Irawan and Anggunmeka Luhur Prasasti
Page: 6991-6997 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

Money is the most commonly used means of payment by the public. But without denying fake money is widely circulated and there are still many people who are less accurate in recognizing the authenticity of the money. This will be bad for social life as we known that money is main payment that can use by everyone. For people with disabilities that lack of visual itself will be hard to know the identity from the money. With this problem in this research will be designed and implemented an Android based mobile application that can recognize currency with image. Applications designed using the Scale Invariant Feature Transform (SIFT) method that can provide information to users about their nominal and authenticity of the money using Indonesian. This application can help people who are less aware of information about genuine money and people with disabilities to find informations about authenticity of Foreign currency. With this application people with disabilities, also can tell the identity of the money itself with more accurate considering this app has implemented by SIFT method on feature extraction but the process time will be longer because the SIFT method itself has a fairly complicated calculation process. From these complex calculations will also produce better accuracy.


How to cite this article:

Mohammad Rizky Adhiguna, Budhi Irawan and Anggunmeka Luhur Prasasti. Design of Foreign Currency Recognition Application using Scale Invariant Feature Transform (SIFT) Method based on Android (Case Study: Singapore Dollar).
DOI: https://doi.org/10.36478/jeasci.2019.6991.6997
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2019.6991.6997