Thank you and yes indeed. This, coupled with rotation invariance is ideal for design/trademark/logo infringement detection scenarios. This result for example is

Thank you and yes indeed. This, coupled with rotation invariance is ideal for design/trademark/logo infringement detection scenarios. This result for example is against the Indian Trademark database https://imgur.com/gallery/SIAwl https://imgur.com/gallery/SIAwl For photos, there's Tineye of course. Color similarity was trivial and took less than 10 lines of code but the shape similarity metric turned out to be quite challenging and took me months to get a reasonably working version. Most of the methods suggested in literature worked wonderfully against MPEG 7 dataset - http://www.dabi.temple.edu/~shape/MPEG7/dataset.html http://www.dabi.temple.edu/~shape/MPEG7/dataset.html - (Few of them got a precision of almost 8 out of top 10 results!) but fared miserably with large datasets of real world designs.