- How accurate is this AI image detector?
- Accuracy is approximately 85-90% across major generators. It is highest on original uncompressed files and lower on heavily compressed, screenshotted, or social-media re-uploaded images. The multi-signal approach outperforms single-method detectors because each forensic test catches a different type of artifact.
- How can I tell if an image is AI-generated?
- Upload the image and the tool analyzes 5 forensic signals: EXIF metadata (real cameras embed data generators lack), Error Level Analysis (generated images have uniform compression), noise patterns (synthetic noise is non-Gaussian, unlike real sensors), color histograms (unnaturally smooth distributions), and frequency spectrum (spectral artifacts from upsampling). You get a confidence score and an explanation of exactly what each test found.
- Can this detect Midjourney, DALL-E, and Stable Diffusion images?
- Yes, along with Flux, ChatGPT image generation, Adobe Firefly, and other major generators. Each architecture leaves different forensic artifacts: GAN-based models leave frequency artifacts, while diffusion models lack high-frequency sensor detail.
- Can this AI image detector detect deepfakes?
- It can partially detect deepfake images (face swaps in photos). ELA and noise analysis detect the boundary artifacts and noise mismatches where a face was swapped into a real photograph. However, high-quality video deepfakes require frame-by-frame temporal analysis which is beyond the scope of this image-based tool.
- Is this AI image detector free?
- Yes. It is completely free with no signup required, no usage limits, no watermarks, and no ads gating results. All processing runs in your browser — no server costs means no need to charge.
- Is my image uploaded to a server?
- No. All forensic analysis runs locally in your browser using the Canvas API and JavaScript. Your image never leaves your device, is never sent over the network, and is never stored anywhere. This makes it safe for analyzing sensitive or private images.
- What image formats does the AI detector support?
- It supports JPG/JPEG, PNG, WebP, BMP, and TIFF files up to 50MB. For best accuracy, upload the original file format. PNG files from generators and JPG files from cameras both work well.
- Why does my real photo show as AI-generated or uncertain?
- Several types of real images can trigger AI detection signals: heavily filtered or HDR photos, computational photography images (iPhone Night Mode, Google HDR+), screenshots, social media re-uploads (Instagram, Facebook, WhatsApp strip EXIF data), stock photos with heavy retouching, or AI-upscaled photos. The tool includes smart context detection for these scenarios and shows exactly which signals fired so you can make your own informed judgment.
- What is Error Level Analysis (ELA)?
- Error Level Analysis (ELA) is a forensic technique that re-saves an image at a known JPEG quality and measures pixel-level differences between the original and re-compressed version. Real photographs show varied error levels across regions because different parts of the scene have different textures and detail. Generated images show abnormally uniform error patterns because every pixel was produced simultaneously by a neural network rather than captured by a physical sensor.
- How does frequency analysis detect AI-generated images?
- Frequency analysis converts the image to the frequency domain using Discrete Fourier Transform and examines the power spectrum. Natural photographs follow a characteristic 1/f power distribution where energy decreases smoothly with frequency. GAN-based AI generators (like older Midjourney versions) leave periodic checkerboard artifacts from transposed convolution upsampling. Diffusion models (like Stable Diffusion and Flux) produce images with near-natural spectral slopes but consistently lack the high-frequency detail that real camera sensors always capture from texture, grain, and noise.
- Can AI image generators fool this detector?
- AI detection is an ongoing arms race. While current AI generators can produce visually convincing images, most still leave measurable forensic traces in noise patterns, frequency spectra, and compression characteristics. The multi-signal approach is more resilient than single-method detectors because a generator would need to simultaneously fake natural camera noise, proper EXIF metadata, realistic compression artifacts, natural frequency distribution, and appropriate color histograms to avoid all five signals.
- How does this compare to other AI image detectors?
- Most online AI image detectors use a single machine learning model that requires uploading your image to their server. This detector is different: it uses 5 forensic signals analyzed entirely in your browser (no upload), provides transparent explanations for each signal rather than a black-box verdict, handles edge cases like screenshots and social media re-uploads with smart adjustments, and is completely free with no signup. The tradeoff is slightly lower accuracy (~85-90%) compared to large ML models (~95%), but with full privacy and transparency.
- How long does AI image detection take?
- Analysis typically takes 2-3 seconds depending on image size and your device performance. The image is automatically resized to a maximum of 1024px for efficient processing. All computation runs locally in your browser — there is no network latency since nothing is uploaded to a server.
- Can I detect AI-generated profile pictures and avatars?
- Yes, this is a common use case. Fake profile photos typically lack camera EXIF data, have non-Gaussian noise patterns, and show frequency artifacts that this tool detects — useful for screening dating apps, social media accounts, and professional profiles for fake headshots.
