{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/accurate-reconstruction-of-ebsd-datasets-by-a","title":"Accurate reconstruction of EBSD datasets by a multimodal data approach using an evolutionary algorithm","arxiv_id":"1903.02988","date":"2019-03-07","proceeding":null,"authors":["Marie-Agathe Charpagne","Florian Strub","Tresa M. Pollock"],"abstract":"A new method has been developed for the correction of the distortions and/or\nenhanced phase differentiation in Electron Backscatter Diffraction (EBSD) data.\nUsing a multi-modal data approach, the method uses segmented images of the\nphase of interest (laths, precipitates, voids, inclusions) on images gathered\nby backscattered or secondary electrons of the same area as the EBSD map. The\nproposed approach then search for the best transformation to correct their\nrelative distortions and recombines the data in a new EBSD file. Speckles of\nthe features of interest are first segmented in both the EBSD and image data\nmodes. The speckle extracted from the EBSD data is then meshed, and the\nCovariance Matrix Adaptation Evolution Strategy (CMA-ES) is implemented to\ndistort the mesh until the speckles superimpose. The quality of the matching is\nquantified via a score that is linked to the number of overlapping pixels in\nthe speckles. The locations of the points of the distorted mesh are compared to\nthose of the initial positions to create pairs of matching points that are used\nto calculate the polynomial function that describes the distortion the best.\nThis function is then applied to un-distort the EBSD data, and the phase\ninformation is inferred using the data of the segmented speckle. Fast and\nversatile, this method does not require any human annotation and can be applied\nto large datasets and wide areas. Besides, this method requires very few\nassumptions concerning the shape of the distortion function. It can be used for\nthe single compensation of the distortions or combined with the phase\ndifferentiation. The accuracy of this method is of the order of the pixel size.\nSome application examples in multiphase materials with feature sizes down to 1\n$\\mu$m are presented, including Ti-6Al-4V Titanium alloy, Rene 65 and additive\nmanufactured Inconel 718 Nickel-base superalloys.","url_abs":"http://arxiv.org/abs/1903.02988v2","url_pdf":"http://arxiv.org/pdf/1903.02988v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"accurate-reconstruction-of-ebsd-datasets-by-a","repo_url":"https://github.com/MLmicroscopy/distortions","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}