Image Similarity Scanner
Upload two images and get a visual similarity percentage. Detects duplicates, finds pixel-level differences, and generates a diff heatmap.
Image 1
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Runs in your browser
Image 2
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Similarity Score
SSIM structural comparison gives a 0–100% match score.
Diff Heatmap
Visual overlay highlighting exactly where images differ.
100% Client-Side
Both images are processed in your browser. Nothing leaves your device.
How it works
How comparison works
Both images are normalized to the same resolution and converted to luminance, then scored with SSIM (Structural Similarity Index) over a sliding 8×8 window — the score reflects structure, contrast and brightness rather than raw per-channel color distance. The result is a percentage similarity score and a visual heatmap showing exactly where differences exist — highlighted regions indicate edits, crops, retouching, color adjustments, or compression artifacts. The heatmap makes it easy to spot localized changes that would be invisible to the naked eye when viewing images side by side. See our image similarity guide for more comparison techniques.
Common use cases
Find duplicate photos across different exports or album versions — for bulk deduplication of larger sets, try the Duplicate Scanner which uses perceptual hashing to group up to 50 images at once. Verify an image hasn't been tampered with by comparing it to a known original. Check how much quality a compressed version has lost relative to the source file. Detect unauthorized edits in photos submitted for publication. Compare before-and-after retouching to quantify the extent of modifications. Verify that product images across different sales channels are consistent.
Visual vs metadata comparison
The Similarity Scanner compares what images look like — pixel content, color, and structure. The Metadata Comparison tool compares what's inside the files — camera settings, timestamps, GPS, and software history. Use visual comparison when you want to see what changed between two versions of an image. Use metadata comparison when you want to know if two photos came from the same camera or were edited differently.
Tips for accurate comparison
For best results, compare images that started from the same source. Comparing completely different photos will produce low similarity scores that aren't meaningful. When checking for edits, use the highest-quality version available as the baseline. Heavily compressed images will show compression-related differences even if no intentional edits were made. For file-level integrity verification, use a SHA-256 hash to detect any byte-level changes.
Image similarity analysis is a key tool in digital forensics, quality assurance, and content management. Professional photographers use it to compare RAW exports against final deliverables. Legal teams verify that evidence photos haven't been altered by comparing against originals collected at the scene. Design teams check that brand images remain consistent across different platforms and formats. The pixel-level heatmap is particularly valuable because it visualizes exactly where differences occur, turning abstract percentage scores into actionable visual information. For the complete verification toolkit, combine similarity analysis with the Authenticity Checker for editing traces and the photo forensics hub for the full investigation workflow. For hash-level file identity, a SHA-256 hash check tells you instantly whether two files are byte-identical without needing pixel comparison.