How does AI Image Detector V1 work?

AI Image Detector V1 uses an ensemble of 17 detection methods — including machine learning (CNNDetection), PRNU sensor fingerprinting, GAN artifact detection, texture analysis, frequency spectrum analysis, gradient analysis, noise pattern analysis, metadata analysis, and C2PA verification — to determine with 90%+ accuracy whether an image is real or AI-generated.

What AI generators can V1 detect?

V1 can identify images created by popular AI generators including Midjourney, DALL-E, Stable Diffusion, Adobe Firefly, and various GAN-based image generators. The multi-method ensemble approach ensures broad coverage across different AI generation techniques.

What is the difference between V1 and V2?

V1 uses 17 traditional detection methods (ML classifiers, sensor analysis, frequency analysis) and provides numerical confidence scores. V2 uses an LLM (Large Language Model) for deeper visual analysis and provides detailed human-readable reports explaining why an image may be AI-generated.

Is AI Image Detector V1 free?

Yes, AI Image Detector V1 is completely free to use. No registration required. Simply upload any image and get instant results with confidence scores from all 17 detection methods.

What is PRNU sensor fingerprinting?

PRNU (Photo Response Non-Uniformity) is a unique noise pattern created by each camera sensor due to manufacturing imperfections. Real photos contain this fingerprint, while AI-generated images lack it. Our detector analyzes this pattern to distinguish authentic camera photos from synthetic images.

What is C2PA verification?

C2PA (Coalition for Content Provenance and Authenticity) is an open standard for digital content provenance. It embeds cryptographic metadata into images to verify their origin. Our detector checks for C2PA certificates to confirm whether an image has verified provenance from a trusted source.

V1 CLASSIC — 17 METHODS

AI Photo Check

Επαληθεύστε τη γνησιότητα εικόνας με το πρότυπο C2PA

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Μορφές: JPEG, PNG, WebP, GIF, TIFF (Μέγ. 20MB)

New Features

Advanced Detection Tools

DEFAULT

AI Image Detector V2 (LLM)

LLM-powered deep analysis with human-readable reports, SynthID watermark detection, and 30+ languages.

Try V2

LIVE

Deepfake Detector

AI-powered deepfake detection with ELA heatmap visualization. Detects face swaps and AI-generated faces.

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V1 CLASSIC

AI Image Detector V1 (17 Methods)

Classic 17-method ensemble: ML Detection, PRNU, GAN Fingerprinting, Frequency Analysis, C2PA and more.

Try Classic

// Πώς λειτουργεί

Ανέβασμα

Select any image file to analyze

Ανάλυση

17 AI detection methods run in parallel

Αποτέλεσμα

Get instant authenticity verdict

// Our Detection Technology

17 advanced AI detection methods combining machine learning, forensic analysis, and signal processing

ML Detection

22% weight

Neural network trained on millions of AI-generated images

PRNU Analysis

18% weight

Detect unique camera sensor fingerprints

GAN Fingerprint

15% weight

Detect GAN upsampling artifacts and patterns

Texture Analysis

12% weight

LBP pattern analysis for texture anomalies

Ανάλυση συχνότητας

12% weight

DCT spectrum analysis for frequency anomalies

Gradient Analysis

10% weight

Edge detection and texture pattern analysis

Noise Pattern

6% weight

Analyze noise uniformity and distribution

Metadata Analysis

5% weight

EXIF data and AI software signature detection

View All Technologies

// What is C2PA?

C2PA (Coalition for Content Provenance and Authenticity) is an open technical standard for certifying the source and history of media content. Major companies like Adobe, Microsoft, Intel, and Arm use C2PA to embed provenance data into images.

When an AI tool like Adobe Firefly, OpenAI DALL-E, or Google Imagen creates an image, it can embed C2PA metadata indicating it was AI-generated. Our tool reads this metadata to verify image authenticity.

Μέθοδοι ανίχνευσης

90%+

Μέση ακρίβεια

Γλώσσες

<5s

Χρόνος ανάλυσης

// Best Free AI Image Detector Online

AI Photo Check is the most advanced free AI image detector available online. Our AI image detector analyzes photos using 17 detection methods — including machine learning, PRNU sensor fingerprinting, GAN artifact detection, and C2PA verification — to determine whether an image is real or AI-generated.

Whether you need to detect images from Midjourney, DALL-E, Stable Diffusion, Adobe Firefly, or any other AI generator, our AI image detector delivers fast, accurate results. Simply upload any image and get an instant authenticity verdict with confidence scores.

No registration required. No cost. 100% private — your images are analyzed securely and never stored permanently. Available in 30+ languages worldwide.

FAQ 2026

Frequently Asked Questions

Learn how to detect AI-generated photos of people and selfies in 2026 using our advanced detection tools.

How to detect AI generated images in selfies 2026?

In 2026, AI-generated selfies have become incredibly realistic — making detection harder than ever. Here's how to spot them using AI Photo Check:

V2 Method 1: AI Image Detector V2 (LLM-Powered)

Go to AI Image Detector V2 and upload the selfie
The LLM engine performs a deep visual analysis examining:
- Facial micro-expressions — AI often creates unnaturally smooth or frozen expressions
- Skin pore consistency — real skin has irregular pore patterns; AI tends to over-smooth
- Iris reflections — genuine selfies show consistent light reflections in both eyes
- Hair strand rendering — AI struggles with individual hair strands near the hairline
- Ear symmetry & detail — AI often generates simplified or asymmetric ears
- Background-face boundary — look for blending artifacts where face meets background
Get a detailed human-readable report explaining exactly why the selfie may be AI-generated, plus SynthID and C2PA watermark detection results

V1 Method 2: AI Image Detector V1 (16 Methods)

Go to AI Image Detector V1 and upload the same selfie
The system runs 16 independent forensic methods simultaneously:
- PRNU sensor fingerprinting — real cameras leave unique sensor noise absent in AI selfies
- GAN fingerprint detection — identifies generator artifacts from StyleGAN, Stable Diffusion, Flux
- Biometric analysis — checks facial landmark proportions and symmetry anomalies
- Frequency spectrum analysis — AI selfies show unnatural high-frequency patterns
- ML Detection (CNNDetection) — neural network trained on millions of real vs AI images
- Metadata/EXIF analysis — genuine selfies contain camera model, GPS, and shooting parameters
Get numerical confidence scores from each of the 16 methods with a final weighted verdict

💡 Pro tip for 2026: Use both V2 and V1 together for maximum accuracy. V2 provides visual reasoning ("the iris reflections are inconsistent") while V1 provides hard forensic evidence across 16 independent detection methods. This dual approach catches even the most sophisticated AI selfies from the latest generators.

How to detect AI generated photos of people 2026?

AI-generated photos of people in 2026 — from full-body portraits to group shots — require advanced forensic tools that go beyond simple visual inspection. Here's a complete guide:

V2 Method 1: AI Image Detector V2 (LLM-Powered)

Go to AI Image Detector V2 and upload the photo of the person
The LLM performs a comprehensive anatomical and environmental analysis:
- Hands & fingers — AI notoriously struggles with correct finger count, joint bending, and nail detail
- Teeth & mouth — look for irregular tooth count, blurred gum lines, or merged teeth
- Clothing texture & fabric physics — AI often generates impossible folds, floating buttons, or inconsistent patterns
- Background consistency — check for warped architectural lines, floating objects, or impossible perspectives
- Lighting & shadow direction — multiple inconsistent light sources are a strong AI indicator
- Skin texture realism — AI over-smooths or creates repetitive skin texture patterns
- SynthID & C2PA detection — checks for digital watermarks embedded by AI generators like Google Imagen and Adobe Firefly
Receive a detailed report in 30+ languages explaining each finding with a confidence score

V1 Method 2: AI Image Detector V1 (16 Methods)

Go to AI Image Detector V1 and upload the photo
The system runs 16 independent forensic methods designed to detect AI-generated people:
- ML Detection (CNNDetection) — deep learning classifier trained on millions of real vs AI-generated human images
- PRNU analysis — verifies authentic camera sensor noise (AI-generated photos lack sensor fingerprints)
- GAN fingerprinting — detects generator-specific patterns from Midjourney, DALL-E, Stable Diffusion, Flux, and others
- Texture analysis (LBP) — reveals AI smoothing artifacts in skin, clothing, and hair textures
- Gradient analysis — detects unnatural edge transitions in AI-generated skin and clothing boundaries
- Noise pattern analysis — AI images have statistically different noise distributions than real photos
- Frequency analysis — FFT/DCT spectrum reveals AI-specific frequency artifacts invisible to the human eye
- C2PA verification — checks for cryptographic provenance certificates from trusted sources
Get confidence scores from all 16 methods with a weighted final verdict and detailed breakdown

💡 Best practice for 2026: Combine V2 + V1 for the most reliable results. V2 explains why a photo looks AI-generated ("the hands have 6 fingers, shadow angles are inconsistent") while V1 provides hard forensic evidence across 16 scientific detection methods. This approach catches AI photos from the latest generators including Midjourney v7, DALL-E 4, Stable Diffusion 4, Flux Ultra, and Adobe Firefly 3.