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Hello Sarah, hello all, some times ago I had the same problem and came accross this blogpost that gives some advice about how to developp an algorithm that would do that : http://www.hackerfactor.com/blog/index.php?/archives/432-Looks-Like-It.html . The update section on this blogpost has some links to scripts that implement this algorithm. My project was canceled so I can't tell you if it works well but according to comments it can be a good solution. But if you have money to spend on it, http://services.tineye.com/MatchEngine is definitely a good choice as their algorithm is quite good. Hope this helps (and maybe that since my original research is quite old now, there are now packaged tools that do it, I don't know) -- Sylvain Machefert - Web services librarian http://geobib.fr/en Le 16/10/2014 18:38, Kyle Banerjee a écrit : > Could you say something about the type of dup detection you need? Are we > talking true duplicates, or possibly the same image in multiple formats, > cropped, etc? Roughly how many images (thousands, tens of thousands, etc) > and how big are they? Also, what did you try that did not meet your needs? > Thanks, > > kyle > > On Wed, Oct 15, 2014 at 2:56 PM, Shipley, Sarah <[log in to unmask]> > wrote: > >> Hi, >> >> I was wondering if anyone had any recommendations for image de-duping >> software that compares the images rather than checksums. We're using >> Visual Similarity Duplicate Image Finder, but find it's not as accurate as >> we'd like. We have a very large number of images to de-dupe in our photo >> archives and with the current software can't find a balance of comparison >> that finds all the dups without producing a lot of false positives. >> >> >> [cid:[log in to unmask]] >> >> Sarah Shipley, CA >> Digital Asset Manager >> Legislative Department - Office of the City Clerk >> http://www.seattle.gov/leg/clerk/ >> 600 Fourth Avenue, Floor 3 >> PO Box 94728 >> Seattle, WA 98124-4728 >> 206.684.8119 >> >> >> >> >> >> >> >> >> >> >>