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I also developed a service based on the Goldberg paper in the mid 2010s. We flattened and discretized the signature to make it searchable which gave us pretty good results: https://github.com/ProvenanceLabs/image-match

Sorry I haven’t maintained the project in years so it’s unlikely to work out of the box. But who knows, maybe you’ll find something useful here for your project!




Ooh, very cool. Were the quoted insertion rates including the vectorization times, and was that using the ES or Mongo backend?


Oh, and did you explore using more lightness buckets than the 5 from the paper?


The insertion rates were based on the elasticsearch backend, with multiple shards/nodes (using the already flattened image signatures). Don't remember specifics unfortunately. I never tried it with more than 5 lightness buckets, sorry!




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