Effects of image filters on various image datasets

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dc.contributor.authorAbidin D.
dc.date.accessioned2024-07-22T08:09:17Z
dc.date.available2024-07-22T08:09:17Z
dc.date.issued2019
dc.description.abstractImage classification is a very common research area, on which researchers work with various classification techniques. The aim of this study is to apply different filters on four different datasets and evaluate their performances in image classification. The study was performed in WEKA environment with Random Forest algorithm and image filters are applied to the datasets one by one and as a combination. Filter combinations got better performance than applying single filter on data. Filter combinations got the worst result on artworks with a percentage of 83.42%. However they were very successful on classifying the images in natural images dataset with a performance of 99.76%. © 2019 Association for Computing Machinery.
dc.identifier.DOI-ID10.1145/3323933.3324056
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/14764
dc.language.isoEnglish
dc.publisherAssociation for Computing Machinery
dc.subjectClassification (of information)
dc.subjectDecision trees
dc.subjectLearning systems
dc.subjectClassification technique
dc.subjectImage datasets
dc.subjectImage filters
dc.subjectNatural images
dc.subjectRandom forest algorithm
dc.subjectWEKA
dc.subjectImage classification
dc.titleEffects of image filters on various image datasets
dc.typeConference paper

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