What algorithm could be used to identify if images are the “same” or similar, regardless of size?

Question

TinEye, the \"reverse image search engine\", allows you to upload/link to an image and it is able to search through the billion images it has crawled and it will return link

Answer 1

The creator of the FotoForensics site posted this blog post on this topic, it was very useful to me, and showed algorithms that may be good enough for you and that require a lot less work than wavelets and feature extraction.

http://www.hackerfactor.com/blog/index.php?/archives/529-Kind-of-Like-That.html

aHash (also called Average Hash or Mean Hash). This approach crushes the image into a grayscale 8x8 image and sets the 64 bits in the hash based on whether the pixel's value is greater than the average color for the image.

pHash (also called "Perceptive Hash"). This algorithm is similar to aHash but use a discrete cosine transform (DCT) and compares based on frequencies rather than color values.

dHash Like aHash and pHash, dHash is pretty simple to implement and is far more accurate than it has any right to be. As an implementation, dHash is nearly identical to aHash but it performs much better. While aHash focuses on average values and pHash evaluates frequency patterns, dHash tracks gradients.

Answer 2

http://tineye.com/faq#how

Based on this, Igor Krivokon's answer seems to be on the mark.