Simple, Fast, and Scalable Reverse Image Search Using Perceptual Hashes and DynamoDB. Christopher Bong provides a clear explanation of how perceptual hashes can be used to create a string representing the visual content of an image, such that similar images can be identified by calculating a hamming distance between those hashes. He then explains how they built a large-scale system for this at Canva on top of DynamoDB, by splitting those strings into smaller hash windows and using those for efficient bulk lookups of similar candidates.
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