How to Find Duplicate or Near-Duplicate Images

“Are these two images the same?”

It sounds like a simple question, but file size and filename won’t answer it. Two images can be byte-for-byte different yet look identical (re-saved at a different quality), or look nearly identical with one small change. To know whether two images are true duplicates, near-duplicates, or genuinely different, you need to compare what’s actually in them.

Compare two images in three steps

DiffALL gives you a precise answer:

1. Upload the two images you want to check.
2. Read the similarity score — SSIM on a 0–100 scale, designed to match how humans perceive visual similarity.
3. Check the heatmap — if the score isn’t 100%, the heatmap shows you exactly where the two images differ.

No install, free to start.

How to interpret the score

• ~100% — effectively identical (the same image, possibly re-encoded).
• 90–99% — near-duplicate; a small region or a quality/colour shift differs. The heatmap shows where.
• Below ~90% — genuinely different content.

Because SSIM is perceptual, a tiny compression difference won’t drag the score down the way a raw byte comparison would — so “near-duplicate” actually means looks nearly the same.

Handling images that aren’t pixel-aligned

Two copies of an image can differ in size or framing without differing in content. DiffALL’s flexible mode aligns the images first (using feature detection) before comparing, so resized or slightly cropped duplicates are still recognised as duplicates rather than flagged as different.

Common use cases

• Photo library cleanup — decide whether two similar shots are true duplicates.
• Asset management — catch re-uploaded or re-encoded copies of the same image.
• Content moderation — check whether a submitted image matches a known one.
• QA — confirm an exported image is identical to the source.

Try it now

Stop guessing whether two images are the same. Upload both and let DiffALL give you a similarity score — and show you exactly where they differ.