Find Duplicate Images — Detect Similar & Duplicate Photos
Batch-upload images and find duplicates and near-duplicates with perceptual hashing — even resized or slightly recolored copies. Clean up your photo library. Compared locally, no upload.
Duplicate image finding uses a perceptual hash to compute a "fingerprint" for each image, then compares the fingerprints for similarity. That is why resized, compressed, or slightly recolored copies are still recognized (plain name / size dedup cannot do this). Comparison runs entirely in your browser — no upload.
When You Need It
Library Cleanup
Clear out the same photo saved over and over on your phone / PC.
Asset Tidying
Find duplicates within batches of assets to save space.
Near Versions
Spot different sizes / compression versions of the same image.
How It Works
Perceptual Hash + Hamming Distance
Each image is shrunk to a small grayscale thumbnail and turned into a 64-bit dHash fingerprint. The fewer bits two fingerprints differ by (the Hamming distance), the more similar they are. The threshold is adjustable — stricter values only match near-identical images.
Batch Large Sets
Hundreds of images computed one-by-one in the browser can be slow and memory-heavy — keep each batch under about 100.
Duplicate Finder FAQ
Yes. Perceptual hashing is insensitive to scaling, compression, and slight recoloring, so different sizes / qualities of the same image are flagged as near-duplicates.
A smaller threshold is stricter (only near-identical images), a larger one is looser (even similar compositions match). The default is balanced and adjustable.
No hard limit, but computing hundreds locally gets slow — batch them under about 100 each.
No. Fingerprinting and comparison run entirely in your browser.