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MSCSCC-Net: multi-scale contextual spatial-channel correlation network for forgery detection and localization of

Wuyang Shan1, Jingchuan Yue2, Steven X Ding3

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This study introduces a new network to detect image forgeries, even with JPEG compression artifacts. The Multi-Scale Contextual Spatial-Channel Correlation Network (MSCSCC-Net) effectively identifies and removes compression issues while preserving forgery evidence.

Keywords:
Attention mechanismImage forgery detection and localizationJpeg compression recoveryMultiscale mechanism

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Area of Science:

  • Digital Image Forensics
  • Computer Vision
  • Signal Processing

Background:

  • JPEG compression artifacts can obscure digital image forgeries.
  • Existing forgery detection methods struggle with JPEG compression.
  • Accurate detection and localization of forgeries in compressed images remain a challenge.

Purpose of the Study:

  • To develop a novel network for detecting and localizing forgeries in JPEG compressed images.
  • To address the challenge of JPEG artifacts obscuring forgery evidence.
  • To simultaneously remove JPEG artifacts while preserving forgery traces.

Main Methods:

  • Introduced a Multi-Scale Contextual Spatial-Channel Correlation Network (MSCSCC-Net).
  • Employed multi-scale mechanisms to handle varying scales of forged areas.
  • Designed Contextual Spatial Correlation Module (CSCM) and Contextual Channel Correlation Module (CCCM) for feature extraction.
  • Utilized fused features for coarse-to-fine forgery detection and mask generation.
  • Integrated JPEG artifact removal as a network task, ensuring forgery artifact retention.

Main Results:

  • MSCSCC-Net demonstrated improved forgery detection and localization performance.
  • The network effectively distinguished between JPEG artifacts, forgery artifacts, and authentic regions.
  • Simultaneous removal of JPEG artifacts and preservation of forgery evidence was achieved.
  • Experimental results showed superior performance compared to state-of-the-art methods.

Conclusions:

  • MSCSCC-Net offers a robust solution for forgery detection and localization in JPEG compressed images.
  • The proposed network effectively handles scale variations and differentiates between artifact types.
  • The integrated approach of artifact removal and forgery detection enhances overall system performance.