Filigrane IA Invisible & Scanner Forensique de Fréquence
Inspectez les anneaux Fourier, grilles de générateurs, plans de bruit LSB, écarts ELA et fréquences ultrasonores 16–24 kHz directement dans votre navigateur.
Déposer une image ou un fichier audio
Compatible JPEG, PNG, WebP, AVIF, TIFF, BMP, MP3, WAV, M4A, FLAC, OGG. Grille maximale 1024×1024 (~8 Mo RAM).
Garantie Zéro-Téléversement : Tous les calculs s'exécutent localement sur votre appareil.
Contrôles de la Transformée de Fourier 2D
Forensic Signal Metrics
Executive Forensic Triage: How to Detect AI Images & Invisible Watermarks
Instant answers synthesized for researchers, forensic analysts, and search engines verifying synthetic media integrity.
Is this image AI generated?
To verify if an image is AI generated, apply a Two-Layer Forensic Audit: First, inspect Layer 1 (Container Provenance) for C2PA JUMBF manifests, IPTC DigitalSourceType tags, and camera EXIF headers. Second, inspect Layer 2 (Signal Mathematics) using a 2D Fast Fourier Transform (2D FFT) to identify periodic lattice crosshairs from neural upscalers, concentric Fourier carrier rings from latent watermarks (SynthID), and flattened Shannon bit-entropy (< 0.95) in the Least Significant Bit (LSB) plane.
What is an invisible AI frequency watermark (SynthID)?
An invisible AI frequency watermark (e.g., Google DeepMind SynthID, Meta Stable Signature) is an imperceptible signal embedded directly into the mathematical coefficients of an image (Discrete Wavelet Transform sub-bands or Fourier coefficients) or audio waveform during synthesis. Unlike EXIF or C2PA metadata stored in file headers, frequency watermarks alter spatial and spectral relationships, surviving screenshots, cropping, lossy JPEG recompression, and color grading. In 2D FFT spectral analysis, they emerge as circular rings or harmonic halos around the DC center.
How can you detect AI images when metadata is stripped?
When metadata is erased by social networks or screenshotting, detect AI images through frequency-domain and steganographic inspection: (1) 2D FFT exposes high-frequency grid artifacts and starburst crosshairs caused by transposed convolutions and pixel-shuffle decoders; (2) LSB Bit-Plane Slicing calculates Shannon entropy on Bit 0—natural camera sensors exhibit chaotic Poisson noise (~0.98–1.00), while AI generators leave flat zero-entropy dead zones; (3) Error Level Analysis (ELA) exposes localized recompression error disparities caused by AI inpainting or Generative Fill.
Container Provenance (Layer 1) vs Signal Forensics (Layer 2)
Why inspecting metadata alone is no longer enough to detect modern generative AI images and synthetic audio.
| Inspection Dimension | FreeImGen AI Signal Scanner | Layer 1 Metadata (C2PA/EXIF) | Traditional ELA Tools |
|---|---|---|---|
| Google SynthID Detection | 2D FFT Frequency Rings | Invisible to headers | Cannot detect |
| Survives Screenshot / Re-save | Embedded in pixel math | 100% stripped | ~ Degraded by re-save |
| Diffusion Upscaler Artifacts | Crosshairs & harmonic grids | No signal | ~ Inconclusive |
| Suno / Udio Ultrasonic Watermarks | 16–24 kHz STFT Waterfall | Missing in MP3s | Images only |
| Zero-Upload Privacy | Pure Client-Side TS | Local parser | Most upload to cloud |
AI Provenance & Watermark Ecosystem Tools
Seamlessly transition between metadata container inspection, C2PA manifest removal, and signal-level frequency forensics.
AI Metadata Checker
Inspect C2PA JUMBF containers, IPTC DigitalSourceType, and camera EXIF headers before running frequency analysis.
Remove Content Credentials
Sanitize C2PA cryptographic manifests and Adobe Content Credentials without re-encoding or degrading pixel quality.
Instagram AI Info Label Remover
Strip false-flag metadata tags triggering Meta automated "AI Info" badges on genuine photos edited in Lightroom.
Why Instagram Says AI Info on Real Photos
Read the comprehensive investigation explaining how phone camera AI and subtle retouching trigger automated platform warnings.
Approfondissement technique : Stéganographie fréquentielle
Algorithme Cooley-Tukey 2D FFT
Transformée de Fourier bidimensionnelle exécutée en mémoire tampon Float32Array pour un traitement en temps réel.
Foire Aux Questions sur les Filigranes Invisibles
Quelle est la différence entre C2PA et SynthID ?
Le C2PA se trouve dans les en-têtes et peut être effacé par une simple capture d'écran. SynthID est directement encodé dans les coefficients fréquentiels des pixels ou du son.
Mes fichiers sont-ils envoyés sur un serveur ?
Non, jamais. Tout s'exécute localement dans votre navigateur en Web Worker TypeScript.