Gelişmiş Arama

Basit öğe kaydını göster

dc.contributor.authorCevik, Taner
dc.contributor.authorCevik, Nazife
dc.contributor.authorZontul, Metin
dc.date.accessioned2022-11-28T11:42:34Z
dc.date.available2022-11-28T11:42:34Z
dc.date.issued2022en_US
dc.identifier.citationQu, Z., Cheng, Z., Liu, W., & Wang, X. (2019). A novel quantum image steganography algorithm based on exploiting modification direction. Multimedia Tools and Applications, 78(7), 7981-8001.en_US
dc.identifier.issn1380-7501
dc.identifier.urihttps://doi.org/10.1007/s11042-022-14152-9
dc.identifier.urihttps://hdl.handle.net/20.500.12294/3061
dc.description.abstractFace recognition remains critical and up-to-date due to its undeniable contribution to security. Many descriptors, the most vital figures used for face discrimination, have been proposed and continue to be done. This article presents a novel and highly discriminative identifier that can maintain high recognition performance, even under high noise, varying illumination, and expression exposure. By evolving the image into a graph, the feature set is extracted from the resulting graph rather than making inferences directly on the image pixels as done conventionally. The adjacency matrix is created at the outset by considering the pixels’ adjacencies and their intensity values. Subsequently, the weighted-directed graph having vertices and edges denoting the pixels and adjacencies between them is formed. Moreover, the weights of the edges state the intensity differences between the adjacent pixels. Ultimately, information extraction is performed, which indicates the importance of each vertex in the graphic, expresses the importance of the pixels in the entire image, and forms the feature set of the face image. As evidenced by the extensive simulations performed, the proposed graphic-based identifier shows remarkable and competitive performance regarding recognition accuracy, even under extreme conditions such as high noise, variable expression, and illumination compared with the state-of-the-art face recognition methods. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofMultimedia Tools and Applicationsen_US
dc.identifier.doi10.1007/s11042-022-14152-9en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFacial Expressionen_US
dc.subjectFacial Recognitionen_US
dc.subjectGraphsen_US
dc.subjectIlluminationen_US
dc.subjectNoiseen_US
dc.titleA local-holistic graph-based descriptor for facial recognitionen_US
dc.typearticleen_US
dc.departmentMühendislik ve Mimarlık Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.authorid0000-0001-9511-9423en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.institutionauthorCevik, Nazife
dc.authorwosidAAD-9979-2022en_US
dc.authorscopusid56747624400en_US
dc.identifier.wosqualityQ2en_US
dc.identifier.wosWOS:000883287200005en_US
dc.identifier.scopus2-s2.0-85141952143en_US


Bu öğenin dosyaları:

Thumbnail

Bu öğe aşağıdaki koleksiyon(lar)da görünmektedir.

Basit öğe kaydını göster