New measures for comparing matrices and their application to image processing
| dc.contributor.author | Sesma Sara, Mikel | |
| dc.contributor.author | Miguel Turullols, Laura de | |
| dc.contributor.author | Pagola Barrio, Miguel | |
| dc.contributor.author | Burusco Juandeaburre, Ana | |
| dc.contributor.author | Mesiar, Radko | |
| dc.contributor.author | Bustince Sola, Humberto | |
| dc.contributor.department | Automatika eta Konputazioa | eu |
| dc.contributor.department | Institute of Smart Cities - ISC | en |
| dc.contributor.department | Automática y Computación | es_ES |
| dc.contributor.funder | Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa | es |
| dc.date.accessioned | 2018-11-27T07:39:00Z | |
| dc.date.available | 2020-09-01T23:00:10Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | In this work we present the class of matrix resemblance functions, i.e., functions that measure the difference between two matrices. We present two construction methods and study the properties that matrix resemblance functions satisfy, which suggest that this class of functions is an appropriate tool for comparing images. Hence, we present a comparison method for grayscale images whose result is a new image, which enables to locate the areas where both images are equally similar or dissimilar. Additionally, we propose some applications in which this comparison method can be used, such as defect detection in industrial manufacturing processes and video motion detection and object tracking. | en |
| dc.description.sponsorship | This work is partially supported by the research services of Universidad Publica de Navarra and by the project TIN2016-77356-P (AEI/FEDER, UE). R. Mesiar is supported by Slovak grant APVV-14-0013, and by Czech Project LQ1602 “IT4Innovations excellence in science”. | en |
| dc.embargo.lift | 2020-09-01 | |
| dc.embargo.terms | 2020-09-01 | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | 10.1016/j.apm.2018.05.006 | |
| dc.identifier.issn | 0307-904X | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/31513 | |
| dc.language.iso | eng | en |
| dc.publisher | Elsevier | en |
| dc.relation.ispartof | Applied mathematical modelling, vol. 61, september 2018, pp. 498-520 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/ES/1PE/TIN2016-77356/ | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.apm.2018.05.006 | |
| dc.rights | © 2018 Elsevier Inc. The manuscript version is made available under the CC BY-NC-ND 4.0 license | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Matrix resemblance functions | en |
| dc.subject | Restricted equivalence functions | en |
| dc.subject | Inclusion grades | en |
| dc.subject | Fuzzy mathematical morphology | en |
| dc.subject | Defect detection | en |
| dc.subject | Motion detection | en |
| dc.title | New measures for comparing matrices and their application to image processing | es_ES |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
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