Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/15948
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dc.contributor.authorAlazawi, E-
dc.contributor.authorSwash, MR-
dc.contributor.authorAbbod, M-
dc.date.accessioned2018-03-08T16:12:08Z-
dc.date.available2016-
dc.date.available2018-03-08T16:12:08Z-
dc.date.issued2016-
dc.identifier.citationJournal of Computer and Communications, 2016, 04 (06), pp. 49 - 67en_US
dc.identifier.issn2327-5219-
dc.identifier.issn2327-5227-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/15948-
dc.identifier.urihttp://www.scirp.org/journal/PaperInformation.aspx?PaperID=66920-
dc.description.abstractHoloscopic 3D imaging is a true 3D imaging system mimics fly’s eye technique to acquire a true 3D optical model of a real scene. To reconstruct the 3D image computationally, an efficient implementation of an Auto-Feature-Edge (AFE) descriptor algorithm is required that provides an individual feature detector for integration of 3D information to locate objects in the scene. The AFE descriptor plays a key role in simplifying the detection of both edge-based and region-based objects. The detector is based on a Multi-Quantize Adaptive Local Histogram Analysis (MQALHA) algorithm. This is distinctive for each Feature-Edge (FE) block i.e. the large contrast changes (gradients) in FE are easier to localise. The novelty of this work lies in generating a free-noise 3D-Map (3DM) according to a correlation analysis of region contours. This automatically combines the exploitation of the available depth estimation technique with edge-based feature shape recognition technique. The application area consists of two varied domains, which prove the efficiency and robustness of the approach: a) extracting a set of setting feature-edges, for both tracking and mapping process for 3D depthmap estimation, and b) separation and recognition of focus objects in the scene. Experimental results show that the proposed 3DM technique is performed efficiently compared to the state-of-the-art algorithms.en_US
dc.format.extent49 - 67-
dc.language.isoenen_US
dc.publisherSCIENTIFIC RESEARCH PUBLISHINGen_US
dc.subjectHoloscopic 3D Imageen_US
dc.subjectEdge Detectionen_US
dc.subjectAuto-Thresholdingen_US
dc.subjectDepthmapen_US
dc.subjectIntegral Imageen_US
dc.subjectLocal Histogram Analysisen_US
dc.subjectObject Recognitionen_US
dc.subjectDepth Measurementen_US
dc.title3D Depth Measurement for Holoscopic 3D Imaging Systemen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.4236/jcc.2016.46005-
dc.relation.isPartOfJournal of Computer and Communications-
pubs.issue06-
pubs.publication-statusPublished-
pubs.volume04-
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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