From the project's About page [0], it seems a fair amount of ML/DL was involved in creating the database. "We developed a program to recognise printers’ orname

From the project's About page [0], it seems a fair amount of ML/DL was involved in creating the database. "We developed a program to recognise printers’ ornaments and extract them from the full page images into a new database." "The approach adopted here is a morphological one. A series of morphological operations (e.g. filtering, dilution, erosion, etc) is applied on each image followed by a series of heuristics to filter out those connected components that are deemed to be printers ornaments." I followed the trail to the lead software developer, an expert in machine learning and data science. In his past projects page [1], he described this project under the heading "Image Processing": "the problem was to automatically detect and extract printers ornaments from millions of scanned 16th, 17th, and 18th century books" If they would release the dataset of these rough-quality images of printers' ornaments, perhaps someone from the public (i.e., open source) would be daring enough to try generating SVGs. I know practically nothing about deep learning (but curious and willing to learn :), but I'm supposing this wouldn't count as "second-order machine learning".. Edit: Further down the rabbit hole, there do seem to be some promising/interesting work in this direction, such as "Conversion of Bitmaps into Scalable Function Graphics using a Pre-trained Neural Network Database" [2]. --- [0] https://fleuron.lib.cam.ac.uk/about https://fleuron.lib.cam.ac.uk/about [1] https://dirkgorissen.com/projects/ https://dirkgorissen.com/projects/ [2] https://docs.wixstatic.com/ugd/67bc9f_358dcf74893e4021925ff0f8a618069a.pdf https://docs.wixstatic.com/ugd/67bc9f_358dcf74893e4021925ff0...