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Software architecture for time-constrained machine vision applications

dc.contributor.authorUsamentiaga Fernández, Rubén 
dc.contributor.authorMolleda Meré, Julio 
dc.contributor.authorGarcía Martínez, Daniel Fernando 
dc.contributor.authorGonzález Bulnes, Francisco 
dc.date.accessioned2013-08-27T09:55:54Z
dc.date.available2013-08-27T09:55:54Z
dc.date.issued2013
dc.identifier.citationJournal of Electronic Imaging, 22(1), (2013); doi:10.1117/1.JEI.22.1.013001
dc.identifier.issn1017-9909
dc.identifier.urihttp://hdl.handle.net/10651/18403
dc.description.abstractReal-time image and video processing applications require skilled architects, and recent trends in the hardware platform make the design and implementation of these applications increasingly complex. Many frameworks and libraries have been proposed or commercialized to simplify the design and tuning of real-time image processing applications. However, they tend to lack flexibility, because they are normally oriented toward particular types of applications, or they impose specific data processing models such as the pipeline. Other issues include large memory footprints, difficulty for reuse, and inefficient execution on multicore processors. We present a novel software architecture for time-constrained machine vision applications that addresses these issues. The architecture is divided into three layers. The platform abstraction layer provides a high-level application programming interface for the rest of the architecture. The messaging layer provides a message-passing interface based on a dynamic publish/subscribe pattern. A topic-based filtering in which messages are published to topics is used to route the messages from the publishers to the subscribers interested in a particular type of message. The application layer provides a repository for reusable application modules designed for machine vision applications. These modules, which include acquisition, visualization, communication, user interface, and data processing, take advantage of the power of well-known libraries such as OpenCV, Intel IPP, or CUDA. Finally, the proposed architecture is applied to a real machine vision application: a jam detector for steel pickling lines
dc.description.sponsorshipThis work was partially supported by the Asturian Regional Ministry of Education and Science under Project No. PC10-03
dc.language.isoeng
dc.publisherSPIE (Society of Photo-optical Instrumentation Engineers)
dc.relation.ispartofJournal of Electronic Imaging, 22(1)
dc.rights© Rubén Fernández Usamentiaga et al.
dc.rightsCC Reconocimiento – No comercial – Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleSoftware architecture for time-constrained machine vision applicationseng
dc.typeinfo:eu-repo/semantics/article
dc.identifier.local20130123
dc.identifier.doi10.1117/1.JEI.22.1.013001
dc.type.dcmitext
dc.relation.projectIDPrincipado de Asturias/PC10-03
dc.relation.publisherversionhttp://dx.doi.org/10.1117/1.JEI.22.1.013001
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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