Classification of Face Images Using Discrete Cosine Transform

dc.contributor.authorKarhan, Zehra
dc.contributor.authorErgen, Burhan
dc.date.accessioned2026-08-12T17:01:06Z
dc.date.issued2013
dc.departmentFırat Üniversitesi
dc.description21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS
dc.description.abstractIn this study, it is aimed to determine whether a given image belongs to fort hat person. For feature extraction, which is an important part of pattern recognition, feature vector is obtained by using discrete cosine transform after performing preprocess the images on the current face. Based on the of datas obtained from conversion are classified by using 5%, 8%, 10%, and 15%. The nearest neighbor algorithm (KNN) is used in classification process. Face images consist of images that, taken from ORL database, belongs to 40 individuals, each has 10 different images. As a result, high success were obtained by using the few data.
dc.identifier.isbn978-1-4673-5563-6
dc.identifier.isbn978-1-4673-5562-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/11508/47531
dc.identifier.wosWOS:000325005300204
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherIeee
dc.relation.ispartof2013 21St Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectPattern recognition
dc.subjectdiscrete cosinus transform
dc.subjectK NN Classifier
dc.titleClassification of Face Images Using Discrete Cosine Transform
dc.typeConference Object

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