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MLMVN Neural Network Image splice Tamper Detection | ||
| Iraqi Journal of Information Technology | ||
| Article 1, Volume 8, Issue 2, 2018, Pages 51-75 | ||
| Authors | ||
| Intisar Abd Yousif; Salam Abdulnabi Thajeel | ||
| Abstract | ||
| Image splicing is a commonform of image forgery. Such alterations may leave no visual clues of tampering. For first time,the detection of image splicing through verification of consistency of color and pixelsrelation has been explored in this paper. A new tampering (copy - paste and copy move) detection technique was for digital images. The first method mainly relies on an estimation for the CFA interpolation pattern and the pixel correlated values represented as a linear combination of previous pixels were used to detect the tampering in the tested images samples. The Features vectors are act as inputs to the specific MLMVN neural network in order to recognize the tampering location. The proposed system was work with good results (over 90% detection ratio) for 300 images samples. | ||
| Keywords | ||
| neural network; MLMVN Neural Network; image splicing; MLMVN | ||
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