2023
DOI: 10.11591/eei.v12i2.4481
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A comparative study on image forgery-facial retouching

Abstract: Forgery with the digital images is being very easy now days due to the very advanced and open source image editing tools, software and devises which supports a high quality of resolutions. Tempering with digital documents for changing identity or sometimes for fun is increasing day by day as the era is of digital world. Detecting clues of tampering and verifying the authenticity of images is an important issues now-a-days and growing research field. The existing research in the area of digital image forgery id… Show more

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Cited by 2 publications
(1 citation statement)
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“…Moreover, very little research has been carried out till now over the face images which are retouched using photo editing tools. When employing a DL (deep learning) model to identify retouching on facial photos [20], there are many difficulties as presented in Reference [21]: To train the model to recognize retouching accurately, a large number of images, well-labeled metadata, and a facial dataset comprising both legitimate and manipulated photo images are required. In this context, Transfer learning (TL) addresses various challenges and enables optimal detection accuracy [22].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Moreover, very little research has been carried out till now over the face images which are retouched using photo editing tools. When employing a DL (deep learning) model to identify retouching on facial photos [20], there are many difficulties as presented in Reference [21]: To train the model to recognize retouching accurately, a large number of images, well-labeled metadata, and a facial dataset comprising both legitimate and manipulated photo images are required. In this context, Transfer learning (TL) addresses various challenges and enables optimal detection accuracy [22].…”
Section: Literature Reviewmentioning
confidence: 99%