sensor op• Data kinds: fingerprint → image2d
• Call: import fullseye as fs; fs.ledger.fingerprint_strength_map(fingerprint, block: 'int' = 16) -> 'np.ndarray' (to call the implementation directly, import imgforensics; imgforensics.fingerprint_strength_map(fingerprint, block: 'int' = 16) -> 'np.ndarray'; from the registry, opsimgforensics.get("fingerprint_strength_map"))
A map of the fingerprint's effective strength per block (its standard deviation). image2d.
PRNU does not appear in saturated pixels or pitch-black pixels (it is a multiplicative defect, so it needs signal). This map is for seeing "where the fingerprint can say nothing"; matching results in regions with low values are weak. The standard deviation of each non-overlapping block-square block is returned, expanded back to the original (H, W) as block constants (the edges are filled with the value of the edge block).
Measured (tests/test_imgforensics.py::test_strength_map_marks_the_saturated_half, fingerprint built from 8 images of 128x128 with only the left half saturated): mean strength on the saturated side 0.075 vs. 1.409 on the normal side = 18.8 times. That there is no room for PRNU in the left half (it is a multiplicative defect, so it needs signal) shows up directly.
This is also an exit of the fingerprint vocabulary (so as not to create a dead end).
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• image_forensics_audit — py -3.11 examples/image_forensics_audit.py
image2d as input)perceptual_hash · fingerprint_correlate · error_level_map · jpeg_quality_estimate · jpeg_ghost_map · noise_inconsistency_map · copy_move_regions · watermark_embed
sensor)sensor_fingerprint · fingerprint_correlate
*Provenance: imgforensics.py — IMGFORENSICS operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.