Zaid Nidhal Khudhair^1,4, Farhan Mohamed², Amjad Rehman^3,*, Tanzila Saba³, Saeed Ali bahaj³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4135-4147, 2023, DOI:10.32604/cmc.2023.032315

Abstract This paper presents an improved approach for detecting copy-move forgery based on singular value decomposition (SVD). It is a block-based method where the image is scanned from left to right and top to down by a sliding window with a determined size. At each step, the SVD is determined. First, the diagonal matrix’s maximum value (norm) is selected (representing the scaling factor for SVD and a fixed value for each set of matrix elements even when rotating the matrix or scaled). Then, the similar norms are grouped, and each leading group is separated into many subgroups (elements of each subgroup… More >

C. D. Prem Kumar^1,*, S. Saravana Sundaram²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 881-899, 2023, DOI:10.32604/iasc.2023.025766

Abstract The extensive availability of advanced digital image technologies and image editing tools has simplified the way of manipulating the image content. An effective technique for tampering the identification is the copy-move forgery. Conventional image processing techniques generally search for the patterns linked to the fake content and restrict the usage in massive data classification. Contrastingly, deep learning (DL) models have demonstrated significant performance over the other statistical techniques. With this motivation, this paper presents an Optimal Deep Transfer Learning based Copy Move Forgery Detection (ODTL-CMFD) technique. The presented ODTL-CMFD technique aims to derive a DL model for the classification of… More >

Marriam Nawaz¹, Zahid Mehmood^2,*, Tahira Nazir¹, Momina Masood¹, Usman Tariq³, Asmaa Mahdi Munshi⁴, Awais Mehmood¹, Muhammad Rashid⁵

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1927-1944, 2021, DOI:10.32604/cmc.2021.018052

Abstract Copy-move forgery is the most common type of digital image manipulation, in which the content from the same image is used to forge it. Such manipulations are performed to hide the desired information. Therefore, forgery detection methods are required to identify forged areas. We have introduced a novel method for features computation by employing a circular block-based method through local tetra pattern (LTrP) features to detect the single and multiple copy-move attacks from the images. The proposed method is applied over the circular blocks to efficiently and effectively deal with the post-processing operations. It also uses discrete wavelet transform (DWT)… More >

Weijin Tan^1,*, Yunqing Wu¹, Peng Wu¹, Beijing Chen^1,2

Journal of New Media, Vol.1, No.1, pp. 11-25, 2019, DOI:10.32604/jnm.2019.06219

Abstract Digital images can be tampered easily with simple image editing software tools. Therefore, image forensic investigation on the authenticity of digital images’ content is increasingly important. Copy-move is one of the most common types of image forgeries. Thus, an overview of the traditional and the recent copy-move forgery localization methods using passive techniques is presented in this paper. These methods are classified into three types: block-based methods, keypoint-based methods, and deep learning-based methods. In addition, the strengths and weaknesses of these methods are compared and analyzed in robustness and computational cost. Finally, further research directions are discussed. More >