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الرئيسية > Yemeni Paper Currency Recognit...>الوصف

Yemeni Paper Currency Recognition

المصدر: مجلة بحوث جامعة تعز - سلسلة الآداب والعلوم الإنسانية والتطبيقية
الناشر: جامعة تعز
المؤلف الرئيسي: Alnowaini, Ghazi (Author)
مؤلفين آخرين: Alabsi, Aisha (Co-Author)
المجلد/العدد: ع28
محكمة: نعم
الدولة: اليمن
التاريخ الميلادي: 2021
الشهر: سبتمبر
الصفحات: 20 - 29
رقم MD: 1261801
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: EduSearch, AraBase, HumanIndex
مواضيع:
القطاع المصرفي | الأوراق المالية | الصراف الآلي | الخدمات البنكية
كلمات المؤلف المفتاحية:
Yemeni Currency Recognition | Image Processing | SURF | SVM | GLCM and WED | INTRODUCTION
رابط المحتوى:

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المستخلص: "With the great technological advances in colour printing, duplicating and scanning, counterfeit notes haves posed an increasing threat to currency markets all over the world. Yemeni Currency Recognition System (YCRS) is type Pattern Recognition technology that used to identify Paper Currency of Yemeni country. Due to used currencies in day life, Automatic methods for currency recognition has been increasing. The applications of YCRS is pivotal for banking automation in many sections such as Cash counting machine and ATM machine. However, there is a rare research done towards designing and implementing recognition of Yemeni currency. The absence of such currency recognition is a big gap in Yemen. In this paper, Yemeni Currency Recognition System (YCRS) proposes for recognize all denominations of Yemeni currency notes and enhance the bank system such as counting machines by adding some currency notes. This paper offers a technical remedial solution to this problem for all denominations using image processing and machine learning techniques. The system structure consists of five phases: currency image brings, pre-processing, feature extraction, classification and validation. This research done in software engineering lab, faculty of engineering and information technology, Taiz University from period Dec 2019 until March 2020. In this research, we used different methods in Image Processing such as GLCM, SURF and HSV and Machine learning such as SVM. The Accuracy of this system is very high, it was 99% with fast processing speed. YCRS must be accurate and highly-efficient. It will be the second project taken Yemeni currency, however we are the first people used this technique."

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