The problem a searcher is actually trying to solve

If you license imagery from Getty Images, iStock, or Unsplash+, you receive an asset and a license record. The connection between the two is a set of identifiers: the asset ID printed in the license, the file name on download, and the IPTC, XMP, and EXIF metadata written into the file. Getty does this well. Its rights management, model and property releases, editorial provenance, and its more recent adoption of C2PA content credentials on generative output are as thorough as anything in the market.

The limitation being searched for is not a defect in how Getty runs its catalog. It is a property shared by every system that anchors identity to a record attached to the file rather than to the file's own structure. Metadata is severable. Download a licensed image, drop it into a design tool, export a re-encoded JPEG, take a screenshot of it in a browser, or feed it through a generative model, and the IPTC block, the XMP manifest, and the EXIF fields are routinely stripped or rewritten. The pixels a viewer sees are visually identical. The provable link back to the license is gone.

C2PA content credentials, which Getty attaches to some generative output, are the standards-based answer to this and are a genuine improvement. But C2PA is a signed metadata manifest bound to the file. It is designed to be tamper-evident, not transformation-durable: a stripped or absent manifest produces no verifiable claim, and a re-encode that discards the manifest leaves the content itself carrying no recoverable identity. This is an architectural fact about manifest-based provenance, not a criticism of the standard. The manifest and the pixels are separable, and separation is common in ordinary content workflows.

So the real query behind "Getty Images alternative for provenance" is narrow and specific: is there a way to recover an asset's identity and rights status from the pixels themselves, after the metadata is gone?

What Content Anchoring computes instead

The Content Anchoring inventive step, disclosed in PCT International Application No. PCT/US26/28630, derives a content identity from an artifact's internal structure rather than from its storage location, file name, cryptographic key, or attached metadata. The disclosure calls this a unique identifier, or UID, and it is computed as follows.

An image is normalized to a grayscale scalar field and analyzed at three nested grid resolutions (coarse, medium, and fine). From that multi-scale variance flow the pipeline extracts a nine-dimensional variance vector organized into three axes: an energy-distribution axis, a frequency-compaction axis, and a structural-phase-persistence axis derived from a canonicalized gradient-orientation histogram. The image is then decomposed into four quadrants, each fingerprinted independently and sorted rotation-invariantly, and the global and per-quadrant hashes are combined into a 320-bit UID. Because the UID encodes a position in a continuous variance space, cosine similarity between two UIDs is computed directly, without decoding a fixed binary digest.

The consequence is the property the searcher is after. The disclosure states the UID is designed to be stable under format conversion, resolution rescaling within a canonical size, and lossy compression at moderate quality levels, while diverging predictably when the content itself is altered by object insertion, removal, significant cropping, style transfer, or compositional remixing. Nothing is written into the file. There is no manifest to strip, no watermark to transcode away, and no sidecar record to lose. The identity is recomputed from the pixels every time.

This is the architectural difference, stated fairly. Getty's identity model answers "what record is attached to this file." Content Anchoring answers "what is the structural identity of this content, computed from the content," which remains answerable after every attached record is gone.

Where the axes actually differ

It is worth being precise about what this does and does not displace.

What metadata-anchored identity does well and this does not replace. Getty's asset IDs, license terms, model and property releases, and editorial captions are authoritative records of rights and context. A structural UID is not a license, an authorship claim, or a legal determination of ownership; the disclosure is explicit that lineage edge weights are structural signals, not authorship findings. Metadata carries facts the pixels cannot: who to pay, what the usage grant permits, when the release was signed. That layer stays.

What the structural axis adds. Once identity is computed from content, three capabilities follow that a metadata-only system cannot provide for a stripped file:

  • Recovery after transformation. A re-encoded, rescaled, or screenshotted copy still resolves to the same UID band, so a licensed asset stripped of its manifest can still be matched back to its registered identity by recomputing the UID and querying the anchor network with the UID alone, not the raw image.
  • Derivative and composite lineage. The disclosure builds a multi-root lineage graph: a derivative computed from multiple sources is linked to each parent by cosine similarity, with per-quadrant scores that localize which region was modified. This supports remix and partial-reuse tracing across a catalog, distinct from exact-record lookup.
  • Rights-grade admissibility before release. The disclosure interposes a pre-release admissibility engine that evaluates a candidate artifact against signed, versioned policy objects and a variance-indexed exclusion corpus at the commitment boundary, logging every consultation event deterministically. This governs whether content is released, and records why, rather than moderating after exposure. It is a governance layer that post-hoc metadata inspection does not offer.

For a skilled implementer

This section is written so that a practitioner in image provenance can build the approach, which is the point of a dated public disclosure tied to the filing.

The pipeline is enabling end to end. Normalize the artifact to a grayscale floating-point field using perceptual luma weighting (approximately 0.299 red, 0.587 green, 0.114 blue). Compute per-cell variance over 8x8, 16x16, and 32x32 grids; aggregate mean and standard deviation of variance per scale. Derive the X axis from the slope, curvature, and asymptote of mean variance across scale; the Y axis from the rate of change and spread of variance standard deviation plus a variance-floor convergence term; and the Z axis from a canonicalized eight-bin gradient-orientation histogram plus an edge-density and global-variance stability term. Rescale to a 256x256 canvas with letterbox fill and smoothing disabled, canonicalize orientation when the dominant gradient exceeds roughly 0.1 radians, extract four quadrants, hash each with overlapping FNV-variant functions at two quantization scales, sort the quadrant hashes lexicographically, and combine with a multi-segment FNV-64 combiner into a 320-bit UID.

The approach is reasonably broad. The disclosure enumerates embodiments beyond raster images: audio normalized to a mel spectrogram, text mapped to a TF-IDF positional grid with byte-level variance, video handled at both frame level and clip level via a temporal delta vector, streaming handled over sliding windows, and binary and vector and tabular artifacts each reduced to a bounded two-dimensional scalar field processed by the identical pipeline. Variance banding may use five bands or a finer granularity (ten, twenty, one hundred bands, or a continuous slope spectrum). Deployment spans centralized data centers, federated institutional clusters, decentralized peer networks, and mobile edge nodes, and a client-side embodiment computes the full UID in a standard browser using only Canvas 2D and JavaScript arithmetic, transmitting only the UID rather than the raw artifact. Adjacent detection embodiments include screenshot-recapture classification from Z-axis horizontal-vertical bias, orphan detection for structurally unanchored content, and a model-output provenance fingerprint that measures structural proximity between a generated output and indexed training artifacts without model introspection. Any normalization that yields a bounded two-dimensional scalar field falls within scope.

Why this matters as near-duplicates multiply

Generative tooling multiplies the number of visually similar images in circulation, and each generation, re-encode, and screenshot severs another metadata trail. A licensing catalog whose identity model is record-based degrades exactly as its assets travel. A structural identity that is recomputed from content, survives transformation within defined thresholds, and carries a governance layer for pre-release admissibility addresses the specific axis that gets harder, not easier, over time. That is the scope of the comparison: not that Getty does provenance poorly, but that catalog-and-metadata identity and structural-variance identity answer different questions, and the second question is the one that outlives the file's attached records.

Disclosure scope

The invention described here is the Content Anchoring inventive step, disclosed in PCT International Application No. PCT/US26/28630. Every capability attributed above to the invention, including variance-derived UID construction, quadrant decomposition, multi-root lineage, alias resolution, pre-release admissibility, consultation-event logging, and forbidden-content exclusion, is grounded in that specification and is intended as an enabling, dated public disclosure tied to that filing.

References to Getty Images, iStock, Unsplash+, C2PA content credentials, and the stock-imagery and content-provenance markets are provided as external context to situate the disclosure against the current state of the art. Those references describe third-party products and standards accurately at the architectural level and are not claims of the filing, endorsements, or representations about any third party's roadmap. Product and company names are the marks of their respective owners and are used here for identification and comparison only.