Banknote portrait detection using convolutional neural network

Ryutaro Kitagawa, Yoshihiko Mochizuki, Satoshi Iizuka, Edgar Simo Serra, Hiroshi Matsuki, Naotake Natori, Hiroshi Ishikawa

研究成果: Conference contribution

4 引用 (Scopus)

抜粋

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.

元の言語English
ホスト出版物のタイトルProceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
出版者Institute of Electrical and Electronics Engineers Inc.
ページ440-443
ページ数4
ISBN(電子版)9784901122160
DOI
出版物ステータスPublished - 2017 7 19
イベント15th IAPR International Conference on Machine Vision Applications, MVA 2017 - Nagoya, Japan
継続期間: 2017 5 82017 5 12

Other

Other15th IAPR International Conference on Machine Vision Applications, MVA 2017
Japan
Nagoya
期間17/5/817/5/12

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

フィンガープリント Banknote portrait detection using convolutional neural network' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Kitagawa, R., Mochizuki, Y., Iizuka, S., Simo Serra, E., Matsuki, H., Natori, N., & Ishikawa, H. (2017). Banknote portrait detection using convolutional neural network. : Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017 (pp. 440-443). [7986895] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/MVA.2017.7986895