Publication | Open Access
Survey on blind image forgery detection
128
Citations
66
References
2013
Year
Machine VisionImage AnalysisEngineeringPattern RecognitionMushroom GrowthBiometricsBlind TechniquesDigital Image ForensicsInformation ForensicsDigital ForensicsImage ManipulationComputer ScienceMultimedia SecurityImage ForensicsComputer VisionVideo Forensics
With the mushroom growth of state‐of‐the‐art digital image and video manipulations tools, establishing the authenticity of multimedia content has become a challenging issue. Digital image forensics is an increasingly growing research field that symbolises a never ending struggle against forgery and tampering. This survey attempts to cover the blind techniques that have been proposed for exposing forgeries. This work dwells on the detection techniques for three of the most common forgery types, namely copy/move, splicing and retouching.
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