A New Forgery Image Dataset and its Subjective Evaluation

2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET)(2023)

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摘要
The aim of this research paper is to present a new forgery image dataset with a thorough subjective evaluation in detecting manipulated images, considering various parameters. The original images were obtained from public sources, and meaningful forgeries were produced using an image editing platform with three techniques: cut-paste, copy-move, and erase-fill. Both pre-processing and post-processing methods were used to generate fake images. The subjective evaluation revealed that the accuracy of manipulated image detection was affected by various factors, such as user type, image quantity, tampering method, and image resolution, which were analyzed using quantitative data.
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关键词
Forgery Image Dataset,Image Manipulation,Subjective Assessment,Tampering Detection
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