首页> 外文会议>2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives >Image forgery detection based on illumination inconsistencies amp; intrinsic resampling properties
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Image forgery detection based on illumination inconsistencies amp; intrinsic resampling properties

机译:基于照明不一致性和固有重采样特性的图像伪造检测

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摘要

Photographs are used to represent real-world events. Today many powerful image editing software's like Gimp, Photoshop etc. are available. Any kind of images can be manipulated by using these software's. Image composition or splicing is one of the important image manipulation technique. Sometimes these manipulated images are provided as evidence in court and this may cause serious problems. So it is important to check whether the images available are forged or not. So based on the challenges of forgery detection here a new method is proposed which incorporates both the illumination inconsistencies and resampling properties for detecting forged images. Illumination inconsistency is due to the fact that while creating a forged image it is difficult to achieve proper illuminant condition for the entire image. Also while creating a forged image it is often necessary to resize certain portions of image and this requires resampling image into a new sampling lattice. This introduces certain resampling properties which can be measured. This technique can be used in medical as well as forensic applications to check the genuinity of images.
机译:照片用来代表现实世界的事件。今天,许多强大的图像编辑软件(如Gimp,Photoshop等)都可以使用。使用这些软件可以操纵任何类型的图像。图像合成或拼接是重要的图像处理技术之一。有时在法庭上提供这些被操纵的图像作为证据,这可能会导致严重的问题。因此,重要的是检查可用图像是否伪造。因此,基于伪造检测的挑战,在此提出了一种新方法,该方法结合了照明不一致性和重采样特性来检测伪造图像。照明不一致是由于这样的事实,即在创建伪造图像时,很难为整个图像实现适当的照明条件。同样,在创建伪造图像时,通常需要调整图像的某些部分的大小,这需要将图像重新采样为新的采样点阵。这引入了某些可以测量的重采样特性。此技术可用于医疗以及法医应用程序,以检查图像的真实性。

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