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dc.contributor.authorChu, Cen_US
dc.contributor.authorChang, CCen_US
dc.date.accessioned2014-12-08T15:16:46Z-
dc.date.available2014-12-08T15:16:46Z-
dc.date.issued2006-05-01en_US
dc.identifier.issn0091-3286en_US
dc.identifier.urihttp://dx.doi.org/10.1117/1.2205182en_US
dc.identifier.urihttp://hdl.handle.net/11536/12336-
dc.description.abstractAn asymmetric 2+1 pass stereo matching algorithm is proposed for generating a depth map from the input of two real stereo images. In the first pass, the Canny edge detector is used to acquire edge images from the inputs. Component images are then generated from the edge images. The edges of each component in the left component image are cut to obtain asymmetric left and right component images. The concept of a disparity-space image (DSI) by components is introduced and dynamic programming (DP) techniques are applied to match the asymmetric left and right component images. In the second pass, the previous DSI is modified, applying the DP methods to acquire the matched pixel pairs of the matched component pairs, and to generate ground control pairs (GCPs). In the final pass, these GCPs are incorporated into the DP algorithms to determine the optimal path and acquire the depth image. The results show that the proposed approach produces reliable and efficient matching and preserves the shapes of objects effectively for real stereo images. The proposed algorithm makes contours clearer than other conventional methods for real stereo images. (C) 2006 Society of Photo-Optical Instrumentation Engineers.en_US
dc.language.isoen_USen_US
dc.subjectthree-dimensional computer visionen_US
dc.subjectimage-based renderingen_US
dc.subjectshape from stereoen_US
dc.subjectstereo matchingen_US
dc.titleAsymmetric 2+1 pass stereo matching algorithm for real imagesen_US
dc.typeArticleen_US
dc.identifier.doi10.1117/1.2205182en_US
dc.identifier.journalOPTICAL ENGINEERINGen_US
dc.citation.volume45en_US
dc.citation.issue5en_US
dc.citation.epageen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000238662400041-
dc.citation.woscount0-
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