Scalpel Region Detection based on the Location of Color Marks and Edge Detection
Descripción del Articulo
This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to se...
| Autores: | , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2020 |
| Institución: | Consejo Nacional de Ciencia Tecnología e Innovación |
| Repositorio: | CONCYTEC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.concytec.gob.pe:20.500.12390/2492 |
| Enlace del recurso: | https://hdl.handle.net/20.500.12390/2492 https://doi.org/10.1109/INTERCON50315.2020.9220207 |
| Nivel de acceso: | acceso abierto |
| Materia: | Fuzzy Logic Color Thresholds Digital Image Processing Edge Detection http://purl.org/pe-repo/ocde/ford#2.02.06 |
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oai:repositorio.concytec.gob.pe:20.500.12390/2492 |
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CONC |
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CONCYTEC-Institucional |
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| dc.title.none.fl_str_mv |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection |
| title |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection |
| spellingShingle |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection Suarez-Quispe J.C. Fuzzy Logic Color Thresholds Digital Image Processing Edge Detection http://purl.org/pe-repo/ocde/ford#2.02.06 |
| title_short |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection |
| title_full |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection |
| title_fullStr |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection |
| title_full_unstemmed |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection |
| title_sort |
Scalpel Region Detection based on the Location of Color Marks and Edge Detection |
| author |
Suarez-Quispe J.C. |
| author_facet |
Suarez-Quispe J.C. Ramos O.E. |
| author_role |
author |
| author2 |
Ramos O.E. |
| author2_role |
author |
| dc.contributor.author.fl_str_mv |
Suarez-Quispe J.C. Ramos O.E. |
| dc.subject.none.fl_str_mv |
Fuzzy Logic |
| topic |
Fuzzy Logic Color Thresholds Digital Image Processing Edge Detection http://purl.org/pe-repo/ocde/ford#2.02.06 |
| dc.subject.es_PE.fl_str_mv |
Color Thresholds Digital Image Processing Edge Detection |
| dc.subject.ocde.none.fl_str_mv |
http://purl.org/pe-repo/ocde/ford#2.02.06 |
| description |
This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed. © 2020 IEEE. |
| publishDate |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.available.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.issued.fl_str_mv |
2020 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12390/2492 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1109/INTERCON50315.2020.9220207 |
| dc.identifier.scopus.none.fl_str_mv |
2-s2.0-85095427878 |
| url |
https://hdl.handle.net/20.500.12390/2492 https://doi.org/10.1109/INTERCON50315.2020.9220207 |
| identifier_str_mv |
2-s2.0-85095427878 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartof.none.fl_str_mv |
Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
| publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
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reponame:CONCYTEC-Institucional instname:Consejo Nacional de Ciencia Tecnología e Innovación instacron:CONCYTEC |
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Consejo Nacional de Ciencia Tecnología e Innovación |
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CONCYTEC |
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CONCYTEC |
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CONCYTEC-Institucional |
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CONCYTEC-Institucional |
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Repositorio Institucional CONCYTEC |
| repository.mail.fl_str_mv |
repositorio@concytec.gob.pe |
| _version_ |
1844882994572034048 |
| spelling |
Publicationrp06360600rp06285600Suarez-Quispe J.C.Ramos O.E.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2020https://hdl.handle.net/20.500.12390/2492https://doi.org/10.1109/INTERCON50315.2020.92202072-s2.0-85095427878This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed. © 2020 IEEE.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengInstitute of Electrical and Electronics Engineers Inc.Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020info:eu-repo/semantics/openAccessFuzzy LogicColor Thresholds-1Digital Image Processing-1Edge Detection-1http://purl.org/pe-repo/ocde/ford#2.02.06-1Scalpel Region Detection based on the Location of Color Marks and Edge Detectioninfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/2492oai:repositorio.concytec.gob.pe:20.500.12390/24922024-05-30 16:08:43.131http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="88950bf6-1afe-4ffc-80ea-3f5d0ce898d8"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Scalpel Region Detection based on the Location of Color Marks and Edge Detection</Title> <PublishedIn> <Publication> <Title>Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020</Title> </Publication> </PublishedIn> <PublicationDate>2020</PublicationDate> <DOI>https://doi.org/10.1109/INTERCON50315.2020.9220207</DOI> <SCP-Number>2-s2.0-85095427878</SCP-Number> <Authors> <Author> <DisplayName>Suarez-Quispe J.C.</DisplayName> <Person id="rp06360" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Ramos O.E.</DisplayName> <Person id="rp06285" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Institute of Electrical and Electronics Engineers Inc.</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Fuzzy Logic</Keyword> <Keyword>Color Thresholds</Keyword> <Keyword>Digital Image Processing</Keyword> <Keyword>Edge Detection</Keyword> <Abstract>This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed. © 2020 IEEE.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1 |
| score |
13.402391 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
