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CNN Based Image Forgery Detection Using Pre-trained AlexNet Model
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2019
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Unknown Venue
Image ClassificationConvolutional Neural NetworkMachine VisionImage AnalysisMachine LearningEngineeringPattern RecognitionFeature LearningImage ForensicsInformation ForensicsImage ManipulationForged ComponentDeep LearningImage Forgery DetectionComputer Vision
Image forgery detection is an approach for detection and localization of forged component from a manipulated image. To find manipulation or tampering in the original image, an adequate number of features are required to classify the given image is either a forged or non-forged. To achieve this convolutional neural network (CNN) based pre-trained AlexNet model's deep features have been utilized which are efficient and effective, as compared to the existing state-of-the-art approaches on publicly available benchmark dataset MICC-F220. The experiment result shows that the proposed approach using a pre-trained AlexNet model based deep features with Support Vector Machine (SVM) classifier has achieved 93.94% accuracy.