Image tampering detection method and device based on dual-channel U-Net model
A tamper detection, dual-channel technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as inability to effectively identify tampered areas, inability to identify tampering types, and single tampering detection technology, to achieve unity and subjective Sexual defects, strong robustness and generalization ability, and the effect of improving detection performance
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[0053] figure 1 It is a flow chart of a tampered image identification method based on deep learning shown according to an exemplary embodiment, refer to figure 1 As shown, the method includes the following steps:
[0054] Step S1: select a number of unprocessed images as original images, and use image editing software to perform image tampering operations to obtain tampered images.
[0055] Step S2: Perform ground truth image rendering for each tampered image in step S1.
[0056] Step S3: extract the noisy image using the Spatial Rich Model (SRM) method for the tampered image.
[0057] Step S4, build a dual-channel U-Net model, the dual-channel U-Net model includes two channels, channel 1 is a U-Net model, including an encoder and a decoder structure, the input is a tampered image, and the tampered image is extracted by the encoder The RGB feature of the image, and then locate the tampered image area through the binary classification output of the decoder; channel 2 is a co...
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