Detection of Copy-Move Forgery in Digital Images Using Singular Value Decomposition

作     者：Zaid Nidhal Khudhair Farhan Mohamed Amjad Rehman Tanzila Saba Saeed Ali bahaj 

作者机构：Faculty of EngineeringSchool of ComputingUniversity Technology of MalaysiaJohar BahruMalaysia UTM-IRDA MaGICXInstitute of Human Centered EngineeringUniversiti Teknologi MalaysiaMalaysia Artificial Intelligence&Data Analytics Lab CCIS Prince Sultan University RiyadhSaudi Arabia Computer Techniques Engineering DepartmentFaculty of Information TechnologyImam Ja’afar Al-Sadiq UniversityBaghdadIraq 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2023年第74卷第2期

页      面：4135-4147页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：Prince Sultan University, PSU Artificial Intelligence and Data Analytics Lab, Prince Sultan University, AIDA 

主　　题：Forgery image forensic image processing region duplication SVD transformation technological development 

摘      要：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 *** each step,the SVD is ***,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 thematrix or scaled).Then,the similar norms are grouped,and each leading group is separated into many subgroups(elements of each subgroup are neighbors)according to 8-adjacency(the subgroups for each leading group must be far from others by a specific distance).After that,a weight is assigned for each subgroup to classify the image as forgery or ***,the F1 score of the proposed system is measured,reaching 99.1%.This approach is robust against rotation,scaling,noisy images,and illumination *** is compared with other similarmethods and presents very promised results.