A fast and accurate algorithm for copy-move forgery detection

Moussa, Abdullah M.

doi:10.1109/icces.2015.7393060

Cited by 5 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [1] With the advent of numerous effective image processing tools in recent times, digital picture counterfeiting has grown to be a significant social problem. One of the most commonly used methods for manipulating imagesCopying and moving forgery, which involves replicating a portion of that photo and then inserting it onto a variousspot within pasting it onto a different .…”

Section: Literature Surveymentioning

confidence: 99%

“…However, because of the large computations required for the reconstruction and the subsequent SVD, this strategy is unable to deliver high query speed over an extended period of time. Correlation coefficient data are also shown in Table (1) following the application of lowpass filtering attacks using filters with varying window sizes. The correlation acquired by the Liu approach is denoted by correlation (2), while the greatest correlation obtained by the suggested method is denoted by correlation (1).…”

Section: F(w)=vs(w)xut (1 4)mentioning

confidence: 99%

See 1 more Smart Citation

Kernel Block Based Morphing Identification and Elimination In Server

R. Maheshwari,

Dr. D. Banumathy,

Dr. P. Thiyagarajan

et al. 2024

Int J Sci Res Sci Eng Technol

View full text Add to dashboard Cite

The primary stage of duplicated region identification for investigating duplicate and insert image forgeries does the image block match. Because of evolution of highly sophisticated tools, numerous image modifications have been made. When images are difficult to duplicate and transfer, forgeries of those parts may happen. The images are examined closely in the area where they were forged. By using the suggested Gaussian RBF kernel PCA, the segment of the image that is copied and pasted will be known. One of the most significant issues in this step is the high processing time required to locate related locations. This research proposes a digital block-based picture water mark embedding strategy this uses singular value decomposition (SVD), a mathematical technique. There is already embedding a water mark across the entire image using traditional SVD watermarking. The suggested method involves breaking up the partitioning original image into blocks, after which the water mark existindividually inserted into the singular value of each block. Additionally, the employ the temporal complexity calculate the recommended algorithm's performance. The result of the experiment and thecalculation analysisdemonstrate that two layer matching is possible more traditional approaches Similar to lexicographic sorting, illustrate how two-layer matching can be accomplished. . High key points are awarded for the dimensionality of the feature vector representation in the picture matching. The suggested approach eliminates compression, identifies picture features using blurring, and contaminates the image with noise. The most straightforward way to identify image forgeries using editing technology or morphing is through computational efficiency. Numerous tests have shown that the system is more efficient than the one that is already in use. It is helpful for recording historical time intervals with patterns resembling those of a query time range. To obtain an accurate prediction, the system determines the location, MAC address, and IP address of the morphing uploader.

show abstract

Section: Literature Surveymentioning

confidence: 99%

Section: F(w)=vs(w)xut (1 4)mentioning

confidence: 99%

Kernel Block Based Morphing Identification and Elimination In Server

R. Maheshwari,

Dr. D. Banumathy,

Dr. P. Thiyagarajan

et al. 2024

Int J Sci Res Sci Eng Technol

View full text Add to dashboard Cite

show abstract

“…Last, Moussa [64] proposed a new simple method for CMFD using the sum of pixel intensities as feature descriptors. The detection algorithm begins by dividing the target digital image into overlapping square blocks.…”

Section: F Color/intensity-based Techniquesmentioning

confidence: 99%

“…Moreover, the matching algorithm uses g2NN to iterate nearest neighbor tests to look for multiple matches. Moussa [64] introduced a fast CMFD method using simple pixel intensity-based descriptors. k-d tree (with 1-norm distance) was adopted to store all the feature descriptors information and search for nearest neighbors during the matching process.…”

Section: ) Hierarchical Structure-based Techniquesmentioning

confidence: 99%

Copy-Move Forgery Detection: A State-of-the-Art Technical Review and Analysis

Teerakanok

Uehara

2019

IEEE Access

View full text Add to dashboard Cite

This paper presents the state-of-the-art technical reviews and analysis of recent copy-move forgery detection (CMFD) techniques. A new CMFD process pipeline was introduced. In addition, the techniques used in each stage of the CMFD pipeline are summarized and classified into small categories. Furthermore, the tables of comparison are provided as a quick reference. This technical review paper is expected to help provide useful insights and updated information regarding recent advancements in CMFD to researchers in the field.

show abstract