Discriminating Between Computer-Generated Facial Images and Natural Ones Using Smoothness Property and Local Entropy

Discriminating between computer-generated images and natural ones is a crucial problem in digital image forensics. Facial images belong to a special case of this problem. Advances in technology have made it possible for computers to generate realistic multimedia contents that are very difficult to d...

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Published inDigital-Forensics and Watermarking pp. 39 - 50
Main Authors Nguyen, Huy H., Nguyen-Son, Hoang-Quoc, Nguyen, Thuc D., Echizen, Isao
Format Book Chapter
LanguageEnglish
Japanese
Published Cham Springer International Publishing 2016
SeriesLecture Notes in Computer Science
Subjects
Computer-generated image
Face spoofing
Facial image
Image forensics
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Abstract Discriminating between computer-generated images and natural ones is a crucial problem in digital image forensics. Facial images belong to a special case of this problem. Advances in technology have made it possible for computers to generate realistic multimedia contents that are very difficult to distinguish from non-computer generated contents. This could lead to undesired applications such as face spoofing to bypass authentication systems and distributing harmful unreal images or videos on social media. We have created a method for identifying computer-generated facial images that works effectively for both frontal and angled images. It can also be applied to extracted video frames. This method is based on smoothness property of the faces presented by edges and human skin’s characteristic via local entropy. Experiments demonstrated that performance of the proposed method is better than that of state-of-the-art approaches.
AbstractList Discriminating between computer-generated images and natural ones is a crucial problem in digital image forensics. Facial images belong to a special case of this problem. Advances in technology have made it possible for computers to generate realistic multimedia contents that are very difficult to distinguish from non-computer generated contents. This could lead to undesired applications such as face spoofing to bypass authentication systems and distributing harmful unreal images or videos on social media. We have created a method for identifying computer-generated facial images that works effectively for both frontal and angled images. It can also be applied to extracted video frames. This method is based on smoothness property of the faces presented by edges and human skin’s characteristic via local entropy. Experiments demonstrated that performance of the proposed method is better than that of state-of-the-art approaches.
Author Nguyen-Son, Hoang-Quoc
Nguyen, Huy H.
Nguyen, Thuc D.
Echizen, Isao
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Shi, Yun-Qing
Pérez-González, Fernando
Echizen, Isao
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Snippet Discriminating between computer-generated images and natural ones is a crucial problem in digital image forensics. Facial images belong to a special case of...
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StartPage 39
SubjectTerms Computer-generated image
Face spoofing
Facial image
Image forensics
Title Discriminating Between Computer-Generated Facial Images and Natural Ones Using Smoothness Property and Local Entropy
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