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Don't know if TinEye use exactly this one, but SURF is a commonly used algorithm for this purpose.
For each image extract key features (SURF, SIFT, whatever) in a form of numerical vectors associated to each image.
Most likely you want an algorithm with a good locality of the image like for example a space-filling-curve. Not the answer you're looking for?Browse other questions tagged algorithm image search image-processing search-engine or ask your own question.

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Algorithm for matching features to features in database is run and close matches are found.
This sfc subdivide the image into smaller tiles and order and also reduce it complexity to 1-dimension.
Associated list of images to matched features vectors is extracted and presented as links to web images.

Then you want to scan the image in this order and do a fourier transformation of each tile because a transformation into frequencies is easier to save in a database.

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