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dc.contributor.authorChang, JYen_US
dc.contributor.authorCho, CWen_US
dc.date.accessioned2014-12-08T15:42:26Z-
dc.date.available2014-12-08T15:42:26Z-
dc.date.issued2002-05-01en_US
dc.identifier.issn0253-3839en_US
dc.identifier.urihttp://hdl.handle.net/11536/28813-
dc.description.abstractThis paper proposes a two-stage scene analysis scheme using a combined fuzzy logic-based technique. The first stage begins with generating fuzzy rules to describe the scene. Based on these fuzzy classification rules. each image pixel is inferred and then classified to the natural object category with the largest membership degree. The second stage involves a newly derived fuzzy K-nearest neighbor algorithm that further refines the classification result obtained. With this second stage, the proposed system is robust because it is demonstrated to be insensitive to the variations of membership functions and image noise contamination. Simulations of real world images have shown that the proposed scheme is very successful and the results are visually confirmed by human observation. The satisfactory results achieved in this paper suggest the feasibility of developing similar systems for other types of images aiming at image description problems.en_US
dc.language.isoen_USen_US
dc.subjectscene analysisen_US
dc.subjectnatural object classificationen_US
dc.subjectfuzzy rule-based image analysisen_US
dc.subjectfuzzy K-NNen_US
dc.titleScene analysis system using a combined fuzzy logic-based techniqueen_US
dc.typeArticleen_US
dc.identifier.journalJOURNAL OF THE CHINESE INSTITUTE OF ENGINEERSen_US
dc.citation.volume25en_US
dc.citation.issue3en_US
dc.citation.spage297en_US
dc.citation.epage307en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000175756100005-
dc.citation.woscount4-
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