Efficient Banknote Recognition Based on Selection of Discriminative Regions with One-Dimensional Visible-Light Line Sensor

被引：9

作者：

Pham, Tuyen Danh ^{[1
]}

Park, Young Ho ^{[1
]}

Kwon, Seung Yong ^{[1
]}

Park, Kang Ryoung ^{[1
]}

Jeong, Dae Sik ^{[1
]}

Yoon, Sungsoo ^{[2
]}

机构：

[1] Dongguk Univ, Div Elect & Elect Engn, 30 Pildong Ro 1 Gil, Seoul 100715, South Korea

[2] Kisan Elect, Sungsoo 2 Ga 3 Dong, Seoul 133831, South Korea

来源：

SENSORS | 2016年 / 16卷 / 03期

基金：

新加坡国家研究基金会;

关键词：

one-dimensional visible-light line sensor; selection of distinguishable areas; various types of banknote databases; banknote recognition; NEURAL-NETWORK; PAPER CURRENCY; CLASSIFICATION; SYSTEM;

D O I：

10.3390/s16030328

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Banknote papers are automatically recognized and classified in various machines, such as vending machines, automatic teller machines (ATM), and banknote-counting machines. Previous studies on automatic classification of banknotes have been based on the optical characteristics of banknote papers. On each banknote image, there are regions more distinguishable than others in terms of banknote types, sides, and directions. However, there has been little previous research on banknote recognition that has addressed the selection of distinguishable areas. To overcome this problem, we propose a method for recognizing banknotes by selecting more discriminative regions based on similarity mapping, using images captured by a one-dimensional visible light line sensor. Experimental results with various types of banknote databases show that our proposed method outperforms previous methods.

引用

页数：18

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