Fuzzy Metaheuristic Algorithm for Copy - Move Forgery Detection in Image

• Published in: Combinatorial Image Analysis Vol. 12148; pp. 273 - 281
• Main Authors: Milosavljević, Nataša S., Ralević, Nebojša M.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2020; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Clustering; Copy-move forgery detection; Fuzzy metrics; Image forensics; Image processing; VNS
• ISBN: 9783030510015; 3030510018
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-51002-2_20

One of the most common methods for counterfeiting digital images is copy-move forgery detection (CMFD). It implies that part of the image is copied and pasted to another part of the same image. The purpose of such changes is to hide certain image content, or to duplicate image content. The aim of this paper is to propose a new clustering algorithm for edited images. The image is divided into non-overlapping blocks. New fuzzy metric is used to calculate the distance between the blocks. In this research the metaheuristic method of the variable neighbourhood search (VNS) is used for the classification of the block. The aim of the classification is that the division should be on the changed and unchanged blocks. The results of this research are compared with the latest results from the literature dealing with this problem and it is shown that the proposed algorithm gives better results. Publicly available image databases were used. The proposed algorithm was implemented in the Python programming language.