{"id":{"repo_id":"umkc","oai_identifier":"oai:mospace.umsystem.edu:10355/63273"},"canonical_url":"https://search.dev.ndltd.org/etd/umkc/oai:mospace.umsystem.edu:10355/63273","repository":{"repo_id":"umkc","name":"University of Missouri - Kansas City","base_url":"https://mospace.umsystem.edu/oai/request"},"display":{"title":"Framework for Automatic Identification of Paper Watermarks with Chain Codes","abstract":"In this dissertation, I present a new framework for automated description, archiving, and identification of paper watermarks found in historical documents and manuscripts. The early manufacturers of paper have introduced the embedding of identifying marks and patterns as a sign of a distinct origin and perhaps as a signature of quality. Thousands of watermarks have been studied, classified, and archived. Most of the classification categories are based on image similarity and are searchable based on a set of defined contextual descriptors. The novel method presented here is for automatic classification, identification (matching) and retrieval of watermark images based on chain code descriptors (CC). The approach for generation of unique CC includes a novel image preprocessing method to provide a solution for rotation and scale invariant representation of watermarks. The unique codes are truly reversible, providing high ratio lossless compression, fast searching, and image matching. The development of a novel distance measure for CC comparison is also presented. Examples for the complete process are given using the recently acquired watermarks digitized with hyper-spectral imaging of Summa Theologica, the work of Antonino Pierozzi (1389 – 1459). The performance of the algorithm on large datasets is demonstrated using watermarks datasets from well-known library catalogue collections.","abstract_html":"In this dissertation, I present a new framework for automated description, archiving, and identification of paper watermarks found in historical documents and manuscripts. The early manufacturers of paper have introduced the embedding of identifying marks and patterns as a sign of a distinct origin and perhaps as a signature of quality. Thousands of watermarks have been studied, classified, and archived. Most of the classification categories are based on image similarity and are searchable based on a set of defined contextual descriptors. The novel method presented here is for automatic classification, identification (matching) and retrieval of watermark images based on chain code descriptors (CC). The approach for generation of unique CC includes a novel image preprocessing method to provide a solution for rotation and scale invariant representation of watermarks. The unique codes are truly reversible, providing high ratio lossless compression, fast searching, and image matching. The development of a novel distance measure for CC comparison is also presented. Examples for the complete process are given using the recently acquired watermarks digitized with hyper-spectral imaging of Summa Theologica, the work of Antonino Pierozzi (1389 – 1459). The performance of the algorithm on large datasets is demonstrated using watermarks datasets from well-known library catalogue collections.","abstract_has_math":false,"creators":["Doynov, Plamen"],"institution":"University of Missouri--Kansas City","degree_name":"Ph.D.","degree_level":"Doctoral","degree_discipline":"Electrical and Computer Engineering (UMKC)","degree_department":null,"school":null,"contributors":[],"advisors":["Derakhshani, Reza"],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-24T05:17:53Z","subjects":[],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10355/63273","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Derakhshani, Reza"]},{"key":"dc:creator","label":"Author","values":["Doynov, Plamen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-05-17T14:24:23Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-05-17T14:24:23Z"]},{"key":"dc:date.issued","label":"Date","values":["2017"]},{"key":"dc:publisher","label":"Institution","values":["University of Missouri--Kansas City"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering (UMKC)","Telecommunications and Computer Networking (UMKC)"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Kansas City"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10355/63273"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Title from PDF of title page viewed May 21, 2018","Dissertation advisor: Reza Derakhshani","Vita","Includes bibliographical references (pages 220-235)","Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2017"]},{"key":"dc:description.abstract","label":"Abstract","values":["In this dissertation, I present a new framework for automated description, archiving, and identification of paper watermarks found in historical documents and manuscripts. The early manufacturers of paper have introduced the embedding of identifying marks and patterns as a sign of a distinct origin and perhaps as a signature of quality. Thousands of watermarks have been studied, classified, and archived. Most of the classification categories are based on image similarity and are searchable based on a set of defined contextual descriptors. The novel method presented here is for automatic classification, identification (matching) and retrieval of watermark images based on chain code descriptors (CC). The approach for generation of unique CC includes a novel image preprocessing method to provide a solution for rotation and scale invariant representation of watermarks. The unique codes are truly reversible, providing high ratio lossless compression, fast searching, and image matching. The development of a novel distance measure for CC comparison is also presented. Examples for the complete process are given using the recently acquired watermarks digitized with hyper-spectral imaging of Summa Theologica, the work of Antonino Pierozzi (1389 – 1459). The performance of the algorithm on large datasets is demonstrated using watermarks datasets from well-known library catalogue collections."]},{"key":"dc:title","label":"Title","values":["Framework for Automatic Identification of Paper Watermarks with Chain Codes"]}]}],"canonical_facts":{"dc:contributor.advisor":["Derakhshani, Reza"],"dc:creator":["Doynov, Plamen"],"dc:date.accessioned":["2018-05-17T14:24:23Z"],"dc:date.available":["2018-05-17T14:24:23Z"],"dc:date.issued":["2017"],"dc:description":["Title from PDF of title page viewed May 21, 2018","Dissertation advisor: Reza Derakhshani","Vita","Includes bibliographical references (pages 220-235)","Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2017"],"dc:description.abstract":["In this dissertation, I present a new framework for automated description, archiving, and identification of paper watermarks found in historical documents and manuscripts. The early manufacturers of paper have introduced the embedding of identifying marks and patterns as a sign of a distinct origin and perhaps as a signature of quality. Thousands of watermarks have been studied, classified, and archived. Most of the classification categories are based on image similarity and are searchable based on a set of defined contextual descriptors. The novel method presented here is for automatic classification, identification (matching) and retrieval of watermark images based on chain code descriptors (CC). The approach for generation of unique CC includes a novel image preprocessing method to provide a solution for rotation and scale invariant representation of watermarks. The unique codes are truly reversible, providing high ratio lossless compression, fast searching, and image matching. The development of a novel distance measure for CC comparison is also presented. Examples for the complete process are given using the recently acquired watermarks digitized with hyper-spectral imaging of Summa Theologica, the work of Antonino Pierozzi (1389 – 1459). The performance of the algorithm on large datasets is demonstrated using watermarks datasets from well-known library catalogue collections."],"dc:identifier.uri":["https://hdl.handle.net/10355/63273"],"dc:language.iso":["en_US"],"dc:publisher":["University of Missouri--Kansas City"],"dc:title":["Framework for Automatic Identification of Paper Watermarks with Chain Codes"],"dc:type":["Thesis"],"thesis:degree_discipline":["Electrical and Computer Engineering (UMKC)","Telecommunications and Computer Networking (UMKC)"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Missouri--Kansas City"]},"updated_at":"2026-07-24T05:17:53Z"}