DC Field | Value | Language |
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dc.contributor.author | Han, JH | - |
dc.contributor.author | Kim, TY | - |
dc.date.accessioned | 2016-03-31T13:08:36Z | - |
dc.date.available | 2016-03-31T13:08:36Z | - |
dc.date.created | 2009-03-18 | - |
dc.date.issued | 2002-03-16 | - |
dc.identifier.issn | 0165-0114 | - |
dc.identifier.other | 2002-OAK-0000002526 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/19165 | - |
dc.description.abstract | Most edge detection methods have parameters (threshold values or standard deviation of Gaussian operator for smoothing) to be set, and these parameters make much influence on the outputs of the detectors. In this paper we propose an objective parameter evaluation measure. We evaluate parameters based on the edge ambiguity measures of existence, location and formation. The existence and location ambiguity measures are derived from comparing fuzzy memberships of edgeness with detected edges, and the formation ambiguity measure assesses the connectedness and the total number of edge point in an edge image with respect to the image size. The parameters which produce the least ambiguous edges of a detection method for an image are selected as significant ones. No iterative visual interaction or prior knowledge of edges are needed for these evaluation measures, The effectiveness of the measures is demonstrated by applying the ambiguity measures to synthetic and real images. (C) 2002 Elsevier Science B.V. All rights reserved. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.relation.isPartOf | FUZZY SETS AND SYSTEMS | - |
dc.subject | image processing | - |
dc.subject | edge detection | - |
dc.subject | parameter evaluation | - |
dc.subject | fuzzy edgeness | - |
dc.subject | DETECTION ALGORITHMS | - |
dc.subject | PERFORMANCE | - |
dc.title | Ambiguity distance: an edge evaluation measure using fuzziness of edges | - |
dc.type | Article | - |
dc.contributor.college | 컴퓨터공학과 | - |
dc.identifier.doi | 10.1016/S0165-0114(01)00037-9 | - |
dc.author.google | Han, JH | - |
dc.author.google | Kim, TY | - |
dc.relation.volume | 126 | - |
dc.relation.issue | 3 | - |
dc.relation.startpage | 311 | - |
dc.relation.lastpage | 324 | - |
dc.contributor.id | 10077431 | - |
dc.relation.journal | FUZZY SETS AND SYSTEMS | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCI | - |
dc.collections.name | Journal Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | FUZZY SETS AND SYSTEMS, v.126, no.3, pp.311 - 324 | - |
dc.identifier.wosid | 000174392400003 | - |
dc.date.tcdate | 2019-01-01 | - |
dc.citation.endPage | 324 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 311 | - |
dc.citation.title | FUZZY SETS AND SYSTEMS | - |
dc.citation.volume | 126 | - |
dc.contributor.affiliatedAuthor | Han, JH | - |
dc.identifier.scopusid | 2-s2.0-0037117198 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 3 | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | image processing | - |
dc.subject.keywordAuthor | edge detection | - |
dc.subject.keywordAuthor | parameter evaluation | - |
dc.subject.keywordAuthor | fuzzy edgeness | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Applied | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematics | - |
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