In this work, the general problem of the detection of features in images is considered. One of the methods, the orientation detection of lines, utilized the Radon transform (sinogram) of an image to detect lines at different angles in an image. The line thickness algorithm was generated by finding a pattern formed by particular lines in an image. The filtering of reconstructed images dealt with the removal of blur and other artifacts that arose in the course of inverting the Radon transform of an image to attempt to obtain the original image.
","abstract_html":"<p>In this work, the general problem of the detection of features in images is considered. One of the methods, the orientation detection of lines, utilized the Radon transform (sinogram) of an image to detect lines at different angles in an image. The line thickness algorithm was generated by finding a pattern formed by particular lines in an image. The filtering of reconstructed images dealt with the removal of blur and other artifacts that arose in the course of inverting the Radon transform of an image to attempt to obtain the original image.</p>","abstract_has_math":false,"creators":["Matz, Sean Cormick"],"institution":null,"degree_name":"Mathematics, PhD","degree_level":"Open Access Dissertation","degree_discipline":"Institute of Mathematical Sciences","degree_department":null,"school":null,"contributors":["John Angus","Ali Nadim"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-01-01T08:00:00Z","date_published":"2020-01-01T08:00:00Z","updated_at":"2026-07-24T01:40:22Z","subjects":["Filtered Images","Fourier Slice Theorem","Fourier Transform","Image Processing","Orientation Detection","Radon Transform","Mathematics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarship.claremont.edu/cgu_etd/632","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["John Angus","Ali Nadim"]},{"key":"dc:creator","label":"Author","values":["Matz, Sean Cormick"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2023-01-01T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Institute of Mathematical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Mathematics, PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Filtered Images","Fourier Slice Theorem","Fourier Transform","Image Processing","Orientation Detection","Radon Transform","Mathematics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarship.claremont.edu/cgu_etd/632"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In this work, the general problem of the detection of features in images is considered. One of the methods, the orientation detection of lines, utilized the Radon transform (sinogram) of an image to detect lines at different angles in an image. The line thickness algorithm was generated by finding a pattern formed by particular lines in an image. The filtering of reconstructed images dealt with the removal of blur and other artifacts that arose in the course of inverting the Radon transform of an image to attempt to obtain the original image.
"]},{"key":"dc:title","label":"Title","values":["Detection and Localization of Linear Features Based on Image Processing Methods"]}]}],"canonical_facts":{"dc:contributor":["John Angus","Ali Nadim"],"dc:creator":["Matz, Sean Cormick"],"dc:date.available":["2023-01-01T08:00:00Z"],"dc:description.abstract":["In this work, the general problem of the detection of features in images is considered. One of the methods, the orientation detection of lines, utilized the Radon transform (sinogram) of an image to detect lines at different angles in an image. The line thickness algorithm was generated by finding a pattern formed by particular lines in an image. The filtering of reconstructed images dealt with the removal of blur and other artifacts that arose in the course of inverting the Radon transform of an image to attempt to obtain the original image.
"],"dc:identifier":["https://scholarship.claremont.edu/cgu_etd/632"],"dc:subject":["Filtered Images","Fourier Slice Theorem","Fourier Transform","Image Processing","Orientation Detection","Radon Transform","Mathematics"],"dc:title":["Detection and Localization of Linear Features Based on Image Processing Methods"],"thesis:degree_discipline":["Institute of Mathematical Sciences"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Mathematics, PhD"]},"updated_at":"2026-07-24T01:40:22Z"}