Banknote portrait detection using convolutional neural network

Ryutaro Kitagawa, Yoshihiko Mochizuki, S. Iizuka, E. Simo-Serra, Hiroshi Matsuki, N. Natori, H. Ishikawa
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引用次数: 9

Abstract

Banknotes generally have different designs according to their denominations. Thus, if characteristics of each design can be recognized, they can be used for sorting banknotes according to denominations. Portrait in banknotes is one such characteristic that can be used for classification. A sorting system for banknotes can be designed that recognizes portraits in each banknote and sort it accordingly. In this paper, our aim is to automate the configuration of such a sorting system by automatically detect portraits in sample banknotes, so that it can be quickly deployed in a new target country. We use Convolutional Neural Networks to detect portraits in completely new set of banknotes robust to variation in the ways they are shown, such as the size and the orientation of the face.
基于卷积神经网络的纸币肖像检测
根据不同的面额,纸币通常有不同的图案。因此,如果每一种设计的特征都能被识别出来,它们就可以用来根据面值对纸币进行分类。纸币上的肖像就是这样一种特征,可以用来分类。可以设计一种钞票分类系统,识别每张钞票上的肖像并进行相应的分类。在本文中,我们的目标是通过自动检测样本钞票中的肖像来自动配置这种分类系统,以便它可以快速部署在新的目标国家。我们使用卷积神经网络来检测全新纸币上的肖像,这些纸币对其展示方式的变化(如脸部的大小和方向)具有很强的抵抗力。
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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