A vision based inspection system using Gaussian mixture model based interactive segmentation

dc.contributor.authorAydin, Ilhan
dc.contributor.authorKaraköse, Mehmet
dc.contributor.authorHamsin, Gaylan Ghazi
dc.contributor.authorAkin, Erhan
dc.date.accessioned2026-08-12T16:08:31Z
dc.date.issued2017
dc.departmentFırat Üniversitesi
dc.description2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 -- 16 September 2017 through 17 September 2017 -- Malatya -- 115012
dc.description.abstractThe quality control is a very important task in industrial systems. When the quality control of a product has been made during production, the manufacturing defects will be minimized. For this purpose, automatic inspection system has been developed. In his study, a new vision based method is proposed for quality control and inspection purposes. The proposed method uses interactive segmentation which the main principle is based on Gaussian mixture models. After the current frame is segmented, some morphological operators will be applied to the segmented image in order to reduce noise. Some geometrical features are calculated and the objects are inspected according to their sizes. The efficiency of the proposed method has been ensured by using real videos. © 2017 IEEE.
dc.identifier.doi10.1109/IDAP.2017.8090193
dc.identifier.isbn978-153861880-6
dc.identifier.scopus2-s2.0-85039924341
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/IDAP.2017.8090193
dc.identifier.urihttps://hdl.handle.net/11508/41257
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofIDAP 2017 - International Artificial Intelligence and Data Processing Symposium
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectAutomatic inspection; Computer vision; Geometric features; Interactive segmentation; Quality control
dc.titleA vision based inspection system using Gaussian mixture model based interactive segmentation
dc.typeConference Object

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