An Efficient Rotation Invariant Feature Extraction Method Based on Ring Projection Technique

dc.authoridUYAR, Murat/0000-0001-7243-7939
dc.contributor.authorAtas, Musa
dc.contributor.authorKaya, Yilmaz
dc.contributor.authorUyar, Murat
dc.date.accessioned2024-12-24T19:23:55Z
dc.date.available2024-12-24T19:23:55Z
dc.date.issued2013
dc.departmentSiirt Üniversitesi
dc.description21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS
dc.description.abstractThis study presents an efficient rotation-invariant feature extraction method based on ring projection technique. The main advantage of this method is to reduce the number of sampling frequency of standard ring projection method. The proposed method is compared with the ring projection and local binary patterns according to the computational speed of the feature extraction and classification accuracy. By incrementally rotating first image of each texture class by 30 and 45 degrees enrich the dataset and yield two texture datasets having totally 1332 and 888 samples from the original Brodatz texture image dataset, respectively. Throughout the study Weka machine learning and data mining tool is utilized. As a classifier Naive Bayes, Bagging and J48 decision tree are used due to their simplicity and speed. Classification performance is evaluated via 10 fold cross validation technique. It is observed that, the proposed method outperforms other alternatives in terms of classification accuracy and feature extraction speed.
dc.identifier.isbn978-1-4673-5563-6
dc.identifier.isbn978-1-4673-5562-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.12604/5747
dc.identifier.wosWOS:000325005300070
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_20241222
dc.subjectrotation-invariant ring projection
dc.subjectlocal binary pattern
dc.subjecttexture classification
dc.subjectpattern recognition
dc.titleAn Efficient Rotation Invariant Feature Extraction Method Based on Ring Projection Technique
dc.typeConference Object

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