Natural scene statistics based publication classification algorithm using convolutional neural network

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1186-1189
Number of pages4
ISBN (Electronic)9781538615423
DOIs
Publication statusPublished - 2018 Feb 5
Event9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia
Duration: 2017 Dec 122017 Dec 15

Publication series

NameProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Volume2018-February

Other

Other9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
CountryMalaysia
CityKuala Lumpur
Period17/12/1217/12/15

Fingerprint

Statistics
Neural networks
Digital devices
Mobile phones

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Information Systems
  • Signal Processing

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 ; Lee, Sanghoon. / 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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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.",
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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; Lee, Sanghoon.

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 proceedingConference contribution

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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). https://doi.org/10.1109/APSIPA.2017.8282209