{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/83344"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/83344","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Dynamics of Biofilm Structure","abstract":"The image analysis approach taken for this work is based on Spatial Gray Level Dependence Matrices (SGLDM). SGLDDI capture the texture on an image in a histogram from which textural descriptors extract features of the spatial organization of the images. With tools from multivariate statistics, the large datasets of image analysis results could be translated into textural fingerprints. Each fingerprint is associated with a developmental state of the biofilm. By following the fingerprints of images over time, we visualize the dynamic developmental history of the biofilm.","abstract_html":"The image analysis approach taken for this work is based on Spatial Gray Level Dependence Matrices (SGLDM). SGLDDI capture the texture on an image in a histogram from which textural descriptors extract features of the spatial organization of the images. With tools from multivariate statistics, the large datasets of image analysis results could be translated into textural fingerprints. Each fingerprint is associated with a developmental state of the biofilm. By following the fingerprints of images over time, we visualize the dynamic developmental history of the biofilm.","abstract_has_math":false,"creators":["Milferstedt, Kim"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil and Environmental Engineering","degree_department":null,"school":null,"contributors":["Eberhard Morgenroth"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T21:04:24Z","date_published":"2015-09-25T21:04:24Z","updated_at":"2026-07-22T22:26:21Z","subjects":["Biology, Microbiology"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3290321"],"render_values":[{"text":"(MiAaPQ)AAI3290321","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/83344","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Eberhard Morgenroth"]},{"key":"dc:creator","label":"Author","values":["Milferstedt, Kim"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T21:04:24Z","10000-01-01","2007"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil and Environmental Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biology, Microbiology"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/83344","(MiAaPQ)AAI3290321"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The image analysis approach taken for this work is based on Spatial Gray Level Dependence Matrices (SGLDM). SGLDDI capture the texture on an image in a histogram from which textural descriptors extract features of the spatial organization of the images. With tools from multivariate statistics, the large datasets of image analysis results could be translated into textural fingerprints. Each fingerprint is associated with a developmental state of the biofilm. By following the fingerprints of images over time, we visualize the dynamic developmental history of the biofilm.","Made available in DSpace on 2015-09-25T21:04:24Z (GMT). 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