Automatic method for detecting specular reflection and motion blur artifacts on endoscopic images using complementary binary classifiers

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dc.contributor.authorTinoco, Nataly
dc.contributor.authorDíaz, Daniela
dc.contributor.authorTarquino, Jonathan
dc.date.accessioned2022-03-02T20:45:27Z
dc.date.available2022-03-02T20:45:27Z
dc.date.issued2021
dc.description.abstractenglishComputer Aided Diagnosis (CAD) tools have demonstrated high performance in the identification of gastrointestinal diseases through endoscopic images (EIs). However, such diagnostic support tools could be affected by image artifacts which may appear in real videos, making that precise artifact detection become in a crucial step for training such supporting tools, even those based on convolutional neural networks (CNN). This work presents an automatic method for detecting the two most frequent artifacts in EIs, specular reflections (SR) and motion blur (MB), as a pre-processing tool for identifying informative frames, suitable for training automatic methods used in CAD tools. The proposed method identifies artifact patterns by utilizing coherence features, between regions with low and high frequencies (brightness, contrast, Comparative Gaussian-Frame Changes- CGFC), and using them to feed two complementary binary classifiers, achieving a precision of 96 % for the identification of SR and 76 % for MB. © 2021 Institution of Engineering and Technology.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1049/icp.2021.1432
dc.identifier.instnameinstname:Universidad El Bosquespa
dc.identifier.reponamereponame:Repositorio Institucional Universidad El Bosquespa
dc.identifier.repourlrepourl:https://repositorio.unbosque.edu.co
dc.identifier.urihttps://hdl.handle.net/20.500.12495/7065
dc.language.isoeng
dc.publisherInstitution of Engineering and Technologyspa
dc.publisher.journalIET Conference Publicationsspa
dc.relation.ispartofseriesIET Conference Publications, Vol 2021, 2021, pag 127-132spa
dc.relation.urihttps://digital-library.theiet.org/content/conferences/10.1049/icp.2021.1432
dc.rights.accessrightshttps://purl.org/coar/access_right/c_abf2
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.accessrightsAcceso abierto
dc.rights.localAcceso abiertospa
dc.subject.keywordsEndoscopic imagesspa
dc.subject.keywordsMotion blurspa
dc.subject.keywordsPattern recognitionspa
dc.subject.keywordsSpecular reflectionsspa
dc.titleAutomatic method for detecting specular reflection and motion blur artifacts on endoscopic images using complementary binary classifiersspa
dc.title.translatedAutomatic method for detecting specular reflection and motion blur artifacts on endoscopic images using complementary binary classifiersspa
dc.type.coarhttps://purl.org/coar/resource_type/c_6501
dc.type.coarversionhttps://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.driverinfo:eu-repo/semantics/article
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.type.localArtículo de revista

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