Importance Of Digital Image Forensics

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With the rapid development of image processing technology, it is getting easier to tamper with digital images without leaving any obvious visual trace. Today, seeing does no longer believe [1]. Image forgery, like any other illegal and pernicious activity, could cause serious harm to society. Digital image forensics is a new emerging field. The aim of image forensics is to detect whether an image has been tampered with. With the widespread usage of high-resolution digital cameras and highly advanced photo editing software, image tampering has become more commonplace, it may be often required to re-sample (resize/rotate/stretch) the image to make it look natural. Therefore, verifying the authenticity of digital images has become a very important issue. JPEG is one of the most commonly used compression schemes in many practical applications. Therefore JPEG image forensics has attracted increasing attention recently. Typically, there are two significant properties available for forensic analysis. The first and the most obvious property are the blocking artifacts in the spatial domain. Due to the block-based processing in the lossy JPEG compression, the discontinuous pixels usually occur in the boundary between two adjacent 8 × 8 blocks. Such a blocking signature can served as an evidence of JPEG compression [2], and some tampering operations [3]. Another important property is the quantization artifacts in the DCT frequency domain. During JPEG compression, each DCT frequency component in the 8 × 8 block is quantized by a quantization step. It will lead to a specific shape of the corresponding DCT histogram. That is, those dequantized coefficients will just cluster in the multiples of the quantization step. Combined with the Laplac... ... middle of paper ... ...ting the disparity map was based on belief propagation and mean shift segmentation [19]. The disparity map and the reference image (JI_L) are segmented into some objects. The objects and the average disparity of these objects are denoted by O_(JI_L)^i & d_(JI_L)^i, respectively, i = 1,2,…,m. If d_(JI_L)^i is in [D_b,D_f ], O_(JI_L)^i is regarded as the main content, O_(JI_L)^i∈O_maipart.If d_(JI_L)^iis not in [D_b,D_f ], O_(JI_L)^i is regarded as the background, O_(JI_L)^i∈O_background. That is, O_(JI_L)^i∈{█(O_mainpart d_(JI_L)^i∈[D_b,D_f ] @O_background d_(JI_L)^i∉[D_b,D_f ] )→(1)┤ A seam is an optimal eight-connected path of pixels on a single JPEG image from top to bottom (vertical) and consisted of one and only one pixel in each row, which guarantees that the JPEG image keeps a rectangle when the seams are removed. In [20], an energy function defines the

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