What Is Reverse Image Search?

Reverse image search (available through Google Images, TinEye, and Bing Visual Search) works by creating a perceptual hash or visual signature of a query image and searching for identical or similar signatures in an indexed database. This approach finds exact copies and visually similar content, but fails for re-encoded files (which have different visual signatures despite similar appearance) and AI-generated content (which is technically a different image). Biometric face scanning — ScanErase's primary method — finds content by matching facial geometry rather than visual similarity, making it effective against re-encoded and AI-generated content.

Key facts about this term

1. Reverse image search finds exact and near-exact copies Google Reverse Image Search and TinEye are useful for finding copies of a specific file across the web. They work best for high-resolution originals that have not been significantly re-encoded.
2. It does not find AI-generated or re-encoded content Perpetrators routinely re-encode NCII before uploading to defeat hash-based detection. Reverse image search misses these copies. Biometric scanning finds them.
3. Use reverse image search as a first step, then biometric scanning Reverse image search is free and fast — use it for an initial assessment. Then use ScanErase's biometric scan for comprehensive detection including re-encoded copies, deepfakes, and content posted without your name.