University of Isfahan Computational Intelligence in Electrical Engineering 2821-0689 5 1 2014 04 21 Detection of Copy-Move Forgery of Digital Images Using Discrete Wavelet Transform and Cosine Transform Coefficients Decomposition Detection of Copy-Move Forgery of Digital Images Using Discrete Wavelet Transform and Cosine Transform Coefficients Decomposition 69 80 15381 FA Mehdi Ghorbani Young researcher and Elites Club, Islamic Azad University, Miyaneh, Iran Mohammad Firouzmand 2 Iranian Research Organization for Science & Technology, Tehran, Iran Ahmad Faraahi Dept. of Computer Engineering, payam Noor University, Tehran, Iran Journal Article 2016 06 14 In Copy-Move forgery, a part of an image is copied and pasted to another place at the same image. This type of manipulation is performed for add details or to conceal unwanted portions of the image. In this paper, we present an improved method using Discrete Wavelet Transform and Cosine Transform Coefficients Decomposition to detect Copy-Move forgery and its challenges. In the proposed method, with utilizing the nature of Wavelet Transform, Singular Value Decomposition and lexicographically a sorting salient improvement is yielded in comparison with relative algorithms. Although a reduction of detection accuracy occurs, it is negligible because of the increase in speed. Since human eye is more sensitive to lower frequencies, Cosine Transform can successfully detect the forged part even when the copied area is manipulated with additional operation such as retouch. Experimental results show that the proposed scheme accurately detects such specific image manipulations as long as the copied region is not rotated or scaled. In Copy-Move forgery, a part of an image is copied and pasted to another place at the same image. This type of manipulation is performed for add details or to conceal unwanted portions of the image. In this paper, we present an improved method using Discrete Wavelet Transform and Cosine Transform Coefficients Decomposition to detect Copy-Move forgery and its challenges. In the proposed method, with utilizing the nature of Wavelet Transform, Singular Value Decomposition and lexicographically a sorting salient improvement is yielded in comparison with relative algorithms. Although a reduction of detection accuracy occurs, it is negligible because of the increase in speed. Since human eye is more sensitive to lower frequencies, Cosine Transform can successfully detect the forged part even when the copied area is manipulated with additional operation such as retouch. Experimental results show that the proposed scheme accurately detects such specific image manipulations as long as the copied region is not rotated or scaled. https://isee.ui.ac.ir/article_15381_ccea4833710c0bb9e136fca395939e2e.pdf