Similar image search by pHash distance in Elasticsearch

I have simulated and implemented a possible solution, which avoids all expensive “fuzzy” queries. Instead at index-time you take N random samples of M bits out of those 64 bits. I guess this is an example of Locality-sensitive hashing. So for each document (and when querying) sample numberx is always taken from same bit positions … Read more

Efficiently find binary strings with low Hamming distance in large set

Question: What do we know about the Hamming distance d(x,y)? Answer: It is non-negative: d(x,y) ≥ 0 It is only zero for identical inputs: d(x,y) = 0 ⇔ x = y It is symmetric: d(x,y) = d(y,x) It obeys the triangle inequality, d(x,z) ≤ d(x,y) + d(y,z) Question: Why do we care? Answer: Because it … Read more

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