Feature Based Indian Currency Detection Using Minimum Weight Distance Classifier

Q2 Engineering
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引用次数: 0

Abstract

The Automated Currency Recognition is of great interest as a number of automated banking systems used by financial institutions make use of it as their main function. A review of the literature on banknote recognition, however, reveals that there are no methods that have been proposed or put into practice for the identification of recently issued bank notes. Real-time applications can benefit from the suggested approach's excellent performance and relative time efficiency. We believe that the composite feature described in this thesis which combines elements of both color and texture is a first in the field of banknote identification. Our contribution is that this research initiative and the suggested technology have made real-time recognition of recently released ultimate development of real-time multi-currency recognition is made feasible by banknotes.
基于特征的最小权重距离分类器的印度货币检测
由于金融机构使用的许多自动银行系统都将自动货币识别作为其主要功能,因此自动货币识别备受关注。然而,对纸币识别文献的回顾表明,目前还没有提出或实施识别最近发行的纸币的方法。实时应用程序可以受益于所建议的方法的优异性能和相对时间效率。我们相信,本文所描述的将颜色和纹理元素结合在一起的复合特征是纸币识别领域的第一个。我们的贡献是,这项研究举措和建议的技术使实时识别成为可能。最近发布的实时多货币识别的最终发展使纸币成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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