Natural scene statistics based publication classification algorithm using convolutional neural network

Hyewon Song; Doyoung Kim; Hyuck Joo Kwon; Sanghoon Lee

doi:10.1109/APSIPA.2017.8282209

Natural scene statistics based publication classification algorithm using convolutional neural network

Hyewon Song, Doyoung Kim, Hyuck Joo Kwon, Sanghoon Lee

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

As digital devices which are capable of viewing contents easily such as mobile phones and tablet PCs have become widespread, publications are being digitized rapidly and the market for digital publications is growing up. However, digital publications are illegally distributed in the form of digital images. It is necessary to identify each digital image for protecting the copyrights of digital publications. We can detect the copyright infringement using publication identification algorithm after applying publication classification. In this paper, we suggest the publication classification method for mainly 4 types such as text, cartoon, webtoon, and regular picture. We use 2-layered CNN for publication classification using histogram images, which are extracted by NSS(Natural Scene Statistics), which usually is used for figuring out distortion in a natural image. We expect that our proposed method will be useful for protecting copyrights of publications.

Original language	English
Title of host publication	Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1186-1189
Number of pages	4
ISBN (Electronic)	9781538615423
DOIs	https://doi.org/10.1109/APSIPA.2017.8282209
Publication status	Published - 2018 Feb 5
Event	9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia Duration: 2017 Dec 12 → 2017 Dec 15

Publication series

Name	Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Volume	2018-February

Other

Other	9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Country/Territory	Malaysia
City	Kuala Lumpur
Period	17/12/12 → 17/12/15

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This research project was supported by Ministry of Culture, Sports and Tourism(MCST) and from Korea Copyright Commission in 2016.

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Human-Computer Interaction
Information Systems
Signal Processing

Access to Document

10.1109/APSIPA.2017.8282209

Cite this

Song, H., Kim, D., Kwon, H. J., & Lee, S. (2018). Natural scene statistics based publication classification algorithm using convolutional neural network. In Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 (pp. 1186-1189). (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017; Vol. 2018-February). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APSIPA.2017.8282209

Song, Hyewon ; Kim, Doyoung ; Kwon, Hyuck Joo et al. / Natural scene statistics based publication classification algorithm using convolutional neural network. Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1186-1189 (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017).

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title = "Natural scene statistics based publication classification algorithm using convolutional neural network",

abstract = "As digital devices which are capable of viewing contents easily such as mobile phones and tablet PCs have become widespread, publications are being digitized rapidly and the market for digital publications is growing up. However, digital publications are illegally distributed in the form of digital images. It is necessary to identify each digital image for protecting the copyrights of digital publications. We can detect the copyright infringement using publication identification algorithm after applying publication classification. In this paper, we suggest the publication classification method for mainly 4 types such as text, cartoon, webtoon, and regular picture. We use 2-layered CNN for publication classification using histogram images, which are extracted by NSS(Natural Scene Statistics), which usually is used for figuring out distortion in a natural image. We expect that our proposed method will be useful for protecting copyrights of publications.",

author = "Hyewon Song and Doyoung Kim and Kwon, {Hyuck Joo} and Sanghoon Lee",

note = "Funding Information: ACKNOWLEDGMENT This research project was supported by Ministry of Culture, Sports and Tourism(MCST) and from Korea Copyright Commission in 2016. Publisher Copyright: {\textcopyright} 2017 IEEE.; 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",

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doi = "10.1109/APSIPA.2017.8282209",

language = "English",

series = "Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Song, H, Kim, D, Kwon, HJ & Lee, S 2018, Natural scene statistics based publication classification algorithm using convolutional neural network. in Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017, vol. 2018-February, Institute of Electrical and Electronics Engineers Inc., pp. 1186-1189, 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017, Kuala Lumpur, Malaysia, 17/12/12. https://doi.org/10.1109/APSIPA.2017.8282209

Natural scene statistics based publication classification algorithm using convolutional neural network. / Song, Hyewon; Kim, Doyoung; Kwon, Hyuck Joo et al.

Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1186-1189 (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017; Vol. 2018-February).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Natural scene statistics based publication classification algorithm using convolutional neural network

AU - Song, Hyewon

AU - Kim, Doyoung

AU - Kwon, Hyuck Joo

AU - Lee, Sanghoon

N1 - Funding Information: ACKNOWLEDGMENT This research project was supported by Ministry of Culture, Sports and Tourism(MCST) and from Korea Copyright Commission in 2016. Publisher Copyright: © 2017 IEEE.

PY - 2018/2/5

Y1 - 2018/2/5

N2 - As digital devices which are capable of viewing contents easily such as mobile phones and tablet PCs have become widespread, publications are being digitized rapidly and the market for digital publications is growing up. However, digital publications are illegally distributed in the form of digital images. It is necessary to identify each digital image for protecting the copyrights of digital publications. We can detect the copyright infringement using publication identification algorithm after applying publication classification. In this paper, we suggest the publication classification method for mainly 4 types such as text, cartoon, webtoon, and regular picture. We use 2-layered CNN for publication classification using histogram images, which are extracted by NSS(Natural Scene Statistics), which usually is used for figuring out distortion in a natural image. We expect that our proposed method will be useful for protecting copyrights of publications.

AB - As digital devices which are capable of viewing contents easily such as mobile phones and tablet PCs have become widespread, publications are being digitized rapidly and the market for digital publications is growing up. However, digital publications are illegally distributed in the form of digital images. It is necessary to identify each digital image for protecting the copyrights of digital publications. We can detect the copyright infringement using publication identification algorithm after applying publication classification. In this paper, we suggest the publication classification method for mainly 4 types such as text, cartoon, webtoon, and regular picture. We use 2-layered CNN for publication classification using histogram images, which are extracted by NSS(Natural Scene Statistics), which usually is used for figuring out distortion in a natural image. We expect that our proposed method will be useful for protecting copyrights of publications.

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BT - Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017

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Y2 - 12 December 2017 through 15 December 2017

ER -

Song H, Kim D, Kwon HJ, Lee S. Natural scene statistics based publication classification algorithm using convolutional neural network. In Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1186-1189. (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017). doi: 10.1109/APSIPA.2017.8282209

Natural scene statistics based publication classification algorithm using convolutional neural network

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