TY - GEN
T1 - Banknote portrait detection using convolutional neural network
AU - Kitagawa, Ryutaro
AU - Mochizuki, Yoshihiko
AU - Iizuka, Satoshi
AU - Simo-Serra, Edgar
AU - Matsuki, Hiroshi
AU - Natori, Naotake
AU - Ishikawa, Hiroshi
N1 - Funding Information:
This work was partially supported by JST CREST.
Publisher Copyright:
© 2017 MVA Organization All Rights Reserved.
PY - 2017/7/19
Y1 - 2017/7/19
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85027891974&partnerID=8YFLogxK
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U2 - 10.23919/MVA.2017.7986895
DO - 10.23919/MVA.2017.7986895
M3 - Conference contribution
AN - SCOPUS:85027891974
T3 - Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
SP - 440
EP - 443
BT - Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IAPR International Conference on Machine Vision Applications, MVA 2017
Y2 - 8 May 2017 through 12 May 2017
ER -