Check TIFF image metadata and AI signals

1. Check the original TIFF before making an export

1. Keep the source file. Work from the scanner output, camera-processing export or original supplied by the publisher. Record where it came from and whether it has already been edited.
2. Open the image checker. In the Image tab, choose Upload image and select one supported .tif or .tiff. Selecting the file starts the check.
3. Read the result with its basis. Open How we checked, then review What we found and Checks run. Distinguish a completed check from an unsupported or unavailable one.
4. Keep a report beside the file. Use Save report or Copy report and record the source, check date and any subsequent export. A later PNG or JPEG is a different file to review.

The TIFF report can show preview unavailable. Open the original in a compatible image application for the visual review; the missing browser thumbnail does not by itself mean the file check failed.

Uploads are private by default and are processed on isGenAI’s server. The main checker is separate from the browser-local editing tools. Read the upload privacy details before including material that needs special handling.

2. Separate a scan’s history from the picture’s origin

A scanner records the material placed in front of it. A photograph of a real scene, a printed AI-generated picture and an edited composite can all become TIFF scans. A scanner name describes a stage in that process; it does not settle what happened before the scan.

For an archive or publication, preserve three useful copies when they exist:

• The supplied original or scan: the starting point for the records you can inspect.
• The edited master: the copy after retouching, restoration, color correction or other changes. Ask which edits used generative tools when that distinction matters.
• The publication export: the version that actually appears in the article, catalogue or website.

Example: a scanned print is restored with a generative editing tool and exported for a catalogue. “Scanned from a print” and “AI was used during restoration” can both be true. Record the stage supported by each finding instead of applying one description to the whole history.

3. Read the saved records without overinterpreting them

TIFF-related metadata can describe equipment, software, dimensions and resolution. Adobe’s TIFF metadata reference defines fields such as Make, Model, Software and XResolution. These fields describe different things: a software name is not a signature, and print resolution is not pixel width.

isGenAI inspects supported EXIF, IPTC and XMP content for recognized AI declarations and checks supported C2PA records. It does not present an exhaustive inventory of every TIFF tag. The file’s records must be readable and contain a supported signal for the corresponding finding to appear.

Read more about signed creation records and why identical pixels can have different metadata. Editable declarations and validated signatures provide different kinds of evidence.

4. Use image measurements to guide a visual review

A supported TIFF can include dimensions, megapixels, brightness, tonal spread, near-black and near-white pixel percentages, transparency and neighboring-pixel differences. Measurements use an oriented sample that fits within 512 × 512 pixels. They describe that sample and do not alter the origin verdict.

In a scanned letter, a high proportion of near-white pixels may simply describe the paper background. A low edge difference can reflect a smooth subject or a small sampled preview. Inspect the original at an appropriate zoom before deciding that detail is missing. These measurements are not an OCR accuracy test, print-color proof or automatic acceptance standard for an archive.

Pixel dimensions and print density answer separate questions. A 3000 × 2400 image placed at 300 pixels per inch corresponds to 10 × 8 inches: divide each pixel dimension by the intended density. That calculation does not establish sharpness or authorship. Use the image diagnostics reference if you need the response fields and unavailable states.

Supported TIFF files and limits

• Format: classic TIFF in either byte order, using .tif or .tiff. BigTIFF is not supported.
• Pages: one page per file, without subimages or image pyramids. Multipage TIFF and files with SubIFDs are rejected rather than treated as a complete review of every stored image.
• Upload size: up to 20 MiB, or 20,971,520 bytes, for the file.
• Decoded size: no more than 40 million pixels. A file with efficient compression can still exceed this limit when decoded.
• Image-model availability: the passive image-model adapter reports TIFF as unsupported media. The checker does not silently convert it into a supported model input.
• Other tools: this support applies to the main image checker. It does not add TIFF to the dedicated saved-prompt extractor or the 25 browser image tools.

For a concrete size check, a US Letter scan at 600 pixels per inch is 5100 × 6600 pixels, or 33.66 million pixels. At 1200 pixels per inch, it is 10,200 × 13,200, or 134.64 million pixels, exceeding the decoded limit even if its compressed file is small. File size and pixel count must both fit.

If a file is rejected, keep the original and create a separate single-page copy within the limits using an application that supports your TIFF. Record any reduction or conversion. Renaming an extension does not convert the contents, and a damaged or unsupported TIFF encoding may still fail.

TIFF checking questions

Sources and scope

The Adobe TIFF metadata reference describes field meanings. Sharp’s input and page controls and metadata documentation describe the image reader used by isGenAI. The upload restrictions above are isGenAI’s own limits; broader format support in a library does not mean every variant is accepted here.

This guide describes a file-review workflow. It does not publish a TIFF detection-accuracy benchmark. Report an incorrect instruction or unsupported example so we can check it against the implementation.