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dc.contributor.authorMannan Saeed Muhammad-
dc.date.accessioned2018-04-25T22:51:00Z-
dc.date.available2018-04-25T22:51:00Z-
dc.date.issued2012-04-
dc.identifier.citationINTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 권: 8 호: 4 페이지: 2777-2788en_US
dc.identifier.issn1349-4198-
dc.identifier.urihttps://pdfs.semanticscholar.org/b622/759135b69f935ae55edbfeb689171f627437.pdf-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/70589-
dc.descriptionKorean Governmenten_US
dc.description.abstractSeveral passive methods like Shape from Focus (SFF) have been proposed for recovering 3-D shape of the objects from their 2-D images. Presence of noise in the images affects the accuracy of shape recovery. Most of the existing approaches show feeble performance when noise is present in the images. In this paper, we propose a new method based On a simple low pass filter, especially designed for SFF methods. The proposed scheme is experimented and evaluated using different image sequences of synthetic and real objects. It provides better results as compared with previous approaches; especially its performance is impressive for noisy images.en_US
dc.description.sponsorshipNational Research Foundation of Koreaen_US
dc.language.isoenen_US
dc.publisherICIC INTERNATIONAL, TOKAI UNIV, 9-1-1, TOROKU, KUMAMOTO, 862-8652, JAPANen_US
dc.subject3D shape reconstructionen_US
dc.subjectShape-from-focusen_US
dc.subjectDepth estimationen_US
dc.subjectRobustnessen_US
dc.subjectFocus measureen_US
dc.subjectNoiseen_US
dc.titleUsing a low pass filter to recover three-dimensional shape from focus in the presence of noiseen_US
dc.typeArticleen_US
dc.relation.no4-
dc.relation.volume8-
dc.relation.page2777-2788-
dc.relation.journalInternational Journal of Innovative Computing, Information and Control-
dc.contributor.googleauthorMuhammad, Mannan Saeed-
dc.contributor.googleauthorMutahira, Husna-
dc.contributor.googleauthorChoi, Tae-Sun-
dc.relation.code2012268287-
dc.sector.campusS-
dc.sector.daehakINDUSTRY-UNIVERSITY COOPERATION FOUNDATION[S]-
dc.sector.departmentRESEARCH INSTITUTE-
dc.identifier.pidmannan-


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