Publication: Image Copy-Move Forgery Detection Algorithms Based on Spatial Feature Domain
Date
2021
Authors
Ahmed I.T.
Hammad B.T.
Jamil N.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Currently, digital image forgery (DIF) become more active due to the advent of powerful image processing tools. On a daily, many images are exchanged through the internet, which makes them susceptible to such effects. One of the most popular of the passive image forgery techniques is copy-move forgery. In the Copy-move forgery, the basic process is copy/paste from one area to another in the same image. In this paper, the proposed image copy-move forgery detection (IC-MFDs) involves five stages: image preprocessing, dividing the image into overlapping blocks, calculating the mean and standard deviation of each block, feature vectors are then sorted lexicographically, then feeding the feature vector to the Support Vector Machine (SVM) classifier to identify the image as authentic or forged. Experiments are performed on a standard dataset of copy move forged images MICC-F220 to evaluate the proposed technique. The findings indicate that the proposed IC-MFDs can be extremely accurate in terms of Detection Accuracy (98.44). We also compare some state-of-the-art approaches with our proposed IC-MFDs. It's noted that the findings obtained are better than these approaches. � 2021 IEEE.
Description
Feature extraction; Signal detection; Support vector machines; Copy-move forgeries; Copy-move forgery detections; Detection accuracy; Image preprocessing; Image processing tools; Mean and standard deviations; Spatial features; State-of-the-art approach; Image processing