Forgery image detection via mask filter banks based CNN

Luyue Wang, Seiichiro Kamata

研究成果

1 被引用数 (Scopus)

抄録

In this paper, we present a new image forgery detection method via a mask filter banks which is consisted with the designed mask filters to extract the features of different channels of image and a modified a ResNet to classify the input image is tempered or not. The proposed model is proved to be capable for copy-move forgery and splicing image detection. In the mask filter layer, we first convert the image from spatial domain to frequency domain, then extract the image edge information of each channel by element-wise with the designed mask matrix. Finally, edge and noise information features of different channels were fused as feature vectors fed to a trained ResNet to do classification. Experiments on three standard datasets: the copy-move forgery image datasets MICC-F220 and MICC-F2000, splicing image manipulation datasets Columbia demonstrate that proposed method get better results than the original colour image as input method and also outperform some existing works.

本文言語English
ホスト出版物のタイトルTenth International Conference on Graphics and Image Processing, ICGIP 2018
編集者Yifei Pu, Hui Yu, Chunming Li, Zhigeng Pan
出版社SPIE
ISBN(電子版)9781510628281
DOI
出版ステータスPublished - 2019 1 1
イベント10th International Conference on Graphics and Image Processing, ICGIP 2018 - Chengdu, China
継続期間: 2018 12 122018 12 14

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
11069
ISSN(印刷版)0277-786X
ISSN(電子版)1996-756X

Conference

Conference10th International Conference on Graphics and Image Processing, ICGIP 2018
国/地域China
CityChengdu
Period18/12/1218/12/14

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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