The difference is the unit being compared
Imagine a portrait cropped into a square avatar. An image-copy engine may recognise that crop as a version of the original photograph. Now imagine a different picture taken a year later, outdoors, with a different expression. That is no longer the same photograph; a face-search engine may compare the facial features instead.
This distinction matters when choosing a tool. You can use copy search to investigate reuse of your artwork, product photography or profile picture. A face-search result is a candidate portrait that needs independent context. It cannot by itself establish a name, relationship or account owner.
Use this decision process
- You want the original publication. Begin with copy-oriented image search and keep the full composition available.
- You want similar designs or objects. Use a general visual search engine, then add relevant text if the interface supports it.
- You want to inspect uses of your own likeness. Consider a face-search provider’s coverage, consent requirements and removal process before uploading.
- You want to verify a person’s claim. Ask for direct, relevant evidence; neither image method replaces that conversation.
Do not use a “no match” result from one method to dismiss a concern that belongs to the other. A new photograph of a familiar face may be absent from a copy index. A recognisable photograph of an object may not contain a usable face at all.
What a score means
A provider’s score describes its own comparison. It is not automatically a percentage probability that two pictures show the same individual. Scores from different engines are not directly comparable without knowing how each is calibrated and evaluated. Our accuracy guide explains the practical consequences.
What Trace currently demonstrates
Trace connects to FaceCheck in test mode and separately offers a fictional example report. The example demonstrates layout and navigation. The API test demonstrates upload, polling, results and cleanup. Neither is a benchmark of full-index search quality.
Before paying for any engine, test a small, permissioned set with known sources and include cases that should produce no match. That helps you distinguish useful results from a convincing interface. See FaceCheck’s own explanation of scores for its terminology.