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Use a reverse-image search index for a one-off public-web check, or a hosted image-matching API for repeated, automated checks. Neither requires you to build a crawler. The important limit: each method searches a particular index or collection, so no results do not prove that a copy does not exist elsewhere online.

Choose the kind of image search you need

These tools search different collections. Pick one based on where you expect the copy to be, rather than treating every reverse-image search as a search of the entire web.

Need Route What it searches
Occasional search across a public-web index TinEye TinEye’s image index
Repeated or integrated public-web checks Copyleaks Image Plagiarism Detection API The service’s matching system; returned results include image and page URLs
Search within selected websites Google Cloud Agent Search Website data configured in a particular app
Compare against your own archive TinEye MatchEngine The customer’s indexed image collection

Search a public-web index manually with TinEye

For a single image, TinEye lets you submit an image by dragging and dropping it, pasting it from the clipboard, uploading a file, or entering an image URL. Results come from TinEye’s own index, not a crawl you run yourself. TinEye says submitted search images are not saved or added to that index; its crawler adds images to the index. See the TinEye tutorial for its submission and search options.

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Use the result controls to find alterations

  • Most Changed: Surface matches that differ more from the query image, which can help when looking for edited variants.
  • Best Match: Find the closest visual matches.
  • Compare Match: Align the query and a result to inspect their differences.
  • Domain filters: Narrow results to a particular website.

These controls help review what the index found; they do not make the index exhaustive. TinEye puts the limitation plainly: “If your search returns no results, that means no matches for your image exist in the TinEye index. Matches might still exist somewhere on the internet, but TinEye hasn’t found them yet.”

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Automate checks with an image-matching API

For a workflow that needs repeated checks or integration into another system, Copyleaks documents an Image Plagiarism Detection API. Its documentation describes full matches—exact or near-exact copies—and partial matches, including cropped, resized, recolored, or otherwise modified images. Results can include image URLs and the web pages where matches were found. Consult the Copyleaks Image Plagiarism Detection API documentation and its API guide for implementation details and current terms.

The documented supported formats are JPG, JPEG, PNG, GIF, BMP, WebP, and ICO, with files up to 20 MB. The API guide also gives an image size and resolution requirement; confirm those requirements, endpoint terms, and limits in the current documentation before building around them. These are vendor specifications, not an independent test of how often the API finds matches. A hosted API outsources matching; it does not guarantee every online copy is indexed or returned.

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Use a bounded corpus when you know where to look

Configured websites: Google Cloud Agent Search

Google Cloud Agent Search supports image queries against a configured app containing website data. The documentation requires Enterprise edition features and Advanced website indexing for image queries. Results can include an image URL and a context link to the page containing it. This route is for the selected website corpus, not a general promise of public-web coverage. Check the Google Cloud image search documentation for current edition and configuration requirements.

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Your own archive: TinEye MatchEngine

MatchEngine is for comparing query images with a collection you have indexed. TinEye describes private collection indexing and partial matches, making it relevant when, for example, an organization wants to compare incoming submissions with its existing archive. Results are bounded by that indexed collection. The product is presented as a paid API; review current plans and volume requirements on the TinEye MatchEngine page.

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Review matches carefully

  1. Open the destination page and inspect the image. A visual match can be a genuinely edited copy, but it can also be a similar image. Compare the actual images rather than relying on a thumbnail or match label alone.
  2. Record the result URL and the date you found it. This gives you a concrete lead to revisit or share.
  3. Verify ownership and licensing separately. Finding an image online does not grant permission to reuse it, and a matching result alone does not establish infringement or identify the original creator with certainty. TinEye also cautions that finding an image does not grant usage rights.

Privacy handling depends on the service. TinEye says it does not save or index submitted search images. Before uploading to another provider or integrating an API, check its current terms for submitted-image handling and retention.

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What a failed search can—and cannot—tell you

A no-result search means the tool did not return a match from the index or collection it searched. It cannot establish that no edited copy exists anywhere online. Coverage varies by service and collection, and a copy may not have been found or indexed.

Image discoverability has other technical limits too. Google Search Central says Google does not index CSS images; that guidance concerns Google’s image discovery and indexing, not the coverage of every reverse-image service. See Google’s image SEO best practices.

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