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Features:

  1. Multiple Detection Methods:

    • Error Level Analysis (ELA)

    • Noise Variance Analysis

    • Color Filter Array (CFA) Analysis

    • JPEG Ghost Detection

    • Deep Learning-based detection (placeholder)

  2. GUI Components:

    • Dual image display (original/processed)

    • Method selection panel

    • Sensitivity adjustment slider

    • Results display area

    • Status bar

  3. Advanced Features:

    • Full analysis combining multiple methods

    • Method comparison window with visualizations

    • Real-time results display

    • Configurable sensitivity settings

  4. Visual Enhancements:

    • Modern dark theme

    • Responsive layout

    • Image resizing and display

    • Color-coded results

Installation Requirements:

bash

pip install opencv-python pip install pillow pip install numpy pip install matplotlib pip install scikit-learn pip install tensorflow # Optional for deep learning

To Use:

  1. Run the script

  2. Click "Load Image" to select an image

  3. Choose a detection method

  4. Adjust sensitivity if needed

  5. Click "Detect Splicing" to analyze

  6. Use "Run Full Analysis" for comprehensive results

  7. Use "Compare Methods" to see different techniques side-by-side

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