Low dimensional DCT and DWT feature based model for detection of image splicing and copy-move forgery
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Low dimensional DCT and DWT feature based model for detection of image splicing and copy-move forgery Sahani Pooja Jaiprakash1 · Madhavi B. Desai2 · Choudhary Shyam Prakash3 · Vipul H. Mistry4 · Kishankumar Lalajibhai Radadiya1 Received: 1 July 2019 / Revised: 23 June 2020 / Accepted: 21 July 2020 / © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Digital images are being used as a prominent carrier of visual information in this age of digitization. Images become more and more omnipresent in everyday life. The images can be easily manipulated due to the accessibility of many internet tools and advanced software. Previously many techniques have been developed to authenticate the images. But all the previous techniques have high dimension of feature vectors. Here, a low dimensional DCT and DWT based features have been introduced to authenticate the images. In this work, we are dealing with both the passive forgery (splicing and copy-move) simultaneously. Features are extracted through image statistics and pixel correlation from DCT and DWT domain. Ensemble classifier has been selected for training and testing. The classifier classifies whether the given images are forged or authentic. Further, it also classifies the forgery in spliced or copy-move. If there is copy-move, the proposed work also perform the region detection using a novel key-point based method. The proposed model gives good detection accuracy and high generalization capability which is independent of image formats. Experimental results demonstrate the performance of proposed work against different post-processing operations like scaling, rotation, and Gaussian noise. Also, the comparative results against different existing methods show the effectiveness of the proposed model. Keywords Image forgery detection · Copy-move · Splicing · DCT · DWT · MSER · Region duplication
1 Introduction Images are important source of information and are more vulnerable since there are many freely available online and off-line tools that are used to manipulate the images. These manipulations can be easily carried out without any obvious proof. It is difficult to identify the forged image with bare eyes most of the time. Manipulation of images could be accomplished in several ways, including copy move, image splicing and retouching [38, 44]. Sahani Pooja Jaiprakash
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Multimedia Tools and Applications
Region duplication is one of the easiest ways of creating fake images and it is also known as copy-move forgery. One or more image regions are copied and pasted to another portion of the same image in region duplication [11]. On the other hand, image splicing is one of the widely used methods for image manipulation where one or more regions of one or more images are combined to create a new image [15]. Image retouching is one of the image forgery tools most widely used for advertisement and aesthetic applications. Retouching is mostly done to impro
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