Authenticating corrupted photo images based on noise parameter estimation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, SW | - |
dc.contributor.author | Jung, HC | - |
dc.contributor.author | Hwang, BW | - |
dc.contributor.author | Lee, SW | - |
dc.date.accessioned | 2021-09-09T06:33:25Z | - |
dc.date.available | 2021-09-09T06:33:25Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2006-05 | - |
dc.identifier.issn | 0031-3203 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/123137 | - |
dc.description.abstract | Photo image authentication is an interesting and demanding field in the computer vision and image processing community. This research is motivated by its wide range of applications, which include smart card authentication systems, biometric passport systems, etc. In this paper, we propose a method of authenticating corrupted photo images based on noise parameter estimation. The proposed method first generates corrupted images by adjusting the noise parameters in the initial training phase. This set of corrupted images and the noise parameters can be represented by a linear combination of the prototypes of the corrupted images and the noise parameters. In the testing phase, the noise parameters of the corrupted photo image can be estimated with a corrupted image and an original image. Finally, we can make a synthesized photo image from the original photo image using the estimated noise parameters and verify it with the corrupted photo image. The experimental results show that the proposed method can estimate the noise parameters accurately and improve the performance of photo image authentication. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.title | Authenticating corrupted photo images based on noise parameter estimation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, SW | - |
dc.identifier.doi | 10.1016/j.patcog.2005.09.017 | - |
dc.identifier.scopusid | 2-s2.0-33244462398 | - |
dc.identifier.wosid | 000236164800014 | - |
dc.identifier.bibliographicCitation | PATTERN RECOGNITION, v.39, no.5, pp.910 - 920 | - |
dc.relation.isPartOf | PATTERN RECOGNITION | - |
dc.citation.title | PATTERN RECOGNITION | - |
dc.citation.volume | 39 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 910 | - |
dc.citation.endPage | 920 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordAuthor | photo image authentication | - |
dc.subject.keywordAuthor | noise models | - |
dc.subject.keywordAuthor | corrupted photo image | - |
dc.subject.keywordAuthor | noise parameter estimation | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.