2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 17 , Issue 1 , PP: 409-424, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Heba Adnan Raheem 1 *
Doi: https://doi.org/10.54216/JISIoT.170129
In the area of digital information, establishing the authenticity of an image has grown to have greater significance as more and more persons have access to sophisticated image editing technologies. There is however a challenge in detecting such a forgery since it is usually very realistic and it is hard to know the difference between the real images and the fake ones. This paper aims at creation of a mechanism of identifying forged images based on Multiple Image Splicing Dataset (MISD) as a reference point. The suggested system will help to improve the results of the forgery detection, paying particular attention to the images processing during some of the pre-processing steps Firstly, converting colors into the hue-based histograms and RGB histograms, and hue-based histograms in an HSV, in comparison between the original and forged image, its HSV histogram, and its grayscale histogram, etc. Lastly, compute MSE and SSIM original and forged image. The implementation results showed that average value of MSE and SSIM metrics on Multiple Image Splicing Dataset (MISD) equal to 184.82 and 0.65 respectively that means the suggested method proved the efficiency of the technique to identify forged images as quickly as possible but still retain accuracy.
Image forgery , Image splicing , Feature extraction , MSE , SSIM
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