Discriminating Between Computer-Generated Facial Images and Natural Ones Using Smoothness Property and Local Entropy
Discriminating Between Computer-Generated Facial Images and Natural Ones Using Smoothness Property and Local Entropy
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DOI：
10.1007/978-3-319-31960-5_4
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发表时间：
2015-10
期刊：
影响因子：
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通讯作者：
H. Nguyen;Hoang-Quoc Nguyen-Son;T. Nguyen;I. Echizen
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文献类型：
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作者：
H. Nguyen;Hoang-Quoc Nguyen-Son;T. Nguyen;I. Echizen
鉴别计算机生成的图像和自然图像是数字图像取证中的一个关键问题。面部图像属于这个问题的一个特例。技术的进步使得计算机能够生成非常难以与非计算机生成的内容区分开的真实多媒体内容。这可能会导致不受欢迎的应用程序，例如面部欺骗以绕过认证系统，并在社交媒体上分发有害的不真实图像或视频。我们已经创建了一种用于识别计算机生成的面部图像的方法，该方法对正面和角度图像都有效。它也可以应用于提取的视频帧。该方法基于人脸边缘的光滑性和局部熵的人体皮肤特征。实验表明，该方法的性能优于国家的最先进的方法。
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.