{"id":{"repo_id":"duquesne","oai_identifier":"oai:dsc.duq.edu:etd-1403"},"canonical_url":"https://search.dev.ndltd.org/etd/duquesne/oai:dsc.duq.edu:etd-1403","repository":{"repo_id":"duquesne","name":"Duquesne","base_url":"https://dsc.duq.edu/do/oai/"},"display":{"title":"Advanced Image Processing Methods for Automated Quantitative Microstructural Analysis","abstract":"Optimization of material properties can be aided by the studying its microstructural behavior. To obtain meaningful information about any given material, a large number of grain boundaries on the order of thousands of grains is required. However, current datasets of grain boundaries are often very limited due to the large amount of human effort required to delineate grain boundaries. Previous attempts to automate the grain boundary detection process using standard image processing techniques required images that were highly optimized for these algorithms. This work seeks to improve previous results by using newer, advanced mathematical methods for image processing. The automated algorithm is compared to standard, manually produced results.","abstract_html":"Optimization of material properties can be aided by the studying its microstructural behavior. To obtain meaningful information about any given material, a large number of grain boundaries on the order of thousands of grains is required. However, current datasets of grain boundaries are often very limited due to the large amount of human effort required to delineate grain boundaries. Previous attempts to automate the grain boundary detection process using standard image processing techniques required images that were highly optimized for these algorithms. This work seeks to improve previous results by using newer, advanced mathematical methods for image processing. The automated algorithm is compared to standard, manually produced results.","abstract_has_math":false,"creators":["Chambers, Jonathan"],"institution":null,"degree_name":"MS","degree_level":"Immediate Access","degree_discipline":"Computational Mathematics","degree_department":null,"school":null,"contributors":["Stacey Levine","John Fleming","Kathleen Taylor"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006-01-01T08:00:00Z","date_published":"2006-01-01T08:00:00Z","updated_at":"2026-07-24T02:09:27Z","subjects":["electron microscopy","grains","image processing"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dsc.duq.edu/etd/390","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stacey Levine","John Fleming","Kathleen Taylor"]},{"key":"dc:creator","label":"Author","values":["Chambers, Jonathan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-08-03T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computational Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Immediate Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["electron microscopy","grains","image processing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dsc.duq.edu/etd/390"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Optimization of material properties can be aided by the studying its microstructural behavior. To obtain meaningful information about any given material, a large number of grain boundaries on the order of thousands of grains is required. However, current datasets of grain boundaries are often very limited due to the large amount of human effort required to delineate grain boundaries. Previous attempts to automate the grain boundary detection process using standard image processing techniques required images that were highly optimized for these algorithms. This work seeks to improve previous results by using newer, advanced mathematical methods for image processing. The automated algorithm is compared to standard, manually produced results."]},{"key":"dc:title","label":"Title","values":["Advanced Image Processing Methods for Automated Quantitative Microstructural Analysis"]}]}],"canonical_facts":{"dc:contributor":["Stacey Levine","John Fleming","Kathleen Taylor"],"dc:creator":["Chambers, Jonathan"],"dc:date.available":["2018-08-03T07:00:00Z"],"dc:description.abstract":["Optimization of material properties can be aided by the studying its microstructural behavior. To obtain meaningful information about any given material, a large number of grain boundaries on the order of thousands of grains is required. However, current datasets of grain boundaries are often very limited due to the large amount of human effort required to delineate grain boundaries. Previous attempts to automate the grain boundary detection process using standard image processing techniques required images that were highly optimized for these algorithms. This work seeks to improve previous results by using newer, advanced mathematical methods for image processing. The automated algorithm is compared to standard, manually produced results."],"dc:identifier":["https://dsc.duq.edu/etd/390"],"dc:language":["English"],"dc:subject":["electron microscopy","grains","image processing"],"dc:title":["Advanced Image Processing Methods for Automated Quantitative Microstructural Analysis"],"thesis:degree_discipline":["Computational Mathematics"],"thesis:degree_level":["Immediate Access"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T02:09:27Z"}