Fingerprint

The fingerprint node computes a perceptual, multi-sector video fingerprint. Unlike a content hash, the fingerprint is robust to transcoding, resolution changes and minor edits, so it can identify the same footage even when the file bytes differ.

Kind

fingerprint

Applies to

Video only

Inputs

None (commonly runs alongside hashing)

Output keys

fingerprint (String)

Requirements

OpenCV / video4j native runtime (video decoding). CPU-bound; no GPU required. Decoding video is I/O- and CPU-heavy for long files.

Persists to

asset_fingerprint_comp (sector 0) + asset_node_result ledger

The perceptual fingerprint is produced by the multi-sector algorithm from the video4j-fingerprint library. The node keeps its own in-heap cache to skip recomputation within a worker’s lifetime.

Configuration

No custom options beyond the common node flags (enabled, …). The node requires a worker with the video4j / OpenCV native libraries available.

Use Cases

  • Near-duplicate video detection — find re-encodes and trims of the same source (see Deduplication).

  • Similarity search — nearest-neighbour lookup over fingerprints to find related clips.

  • Blacklisting — match video content against a fingerprint blacklist even after re-encoding.