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dc.contributor.advisorChen, ZhiQiangeng
dc.contributor.authorChen, Jianfeieng
dc.date.issued2013eng
dc.date.submitted2013 Springeng
dc.descriptionTitle from PDF of title page, viewed on June 12, 2013eng
dc.descriptionThesis advisor: ZhiQiang Cheneng
dc.descriptionVitaeng
dc.descriptionIncludes bibliographic references (pages 76-82)eng
dc.descriptionThesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2013eng
dc.description.abstractMobile imaging has become a very active research topic in recent years thanks to the rapid development of computing and sensing capabilities of mobile devices. This area features multi-disciplinary studies of mobile hardware, imaging sensors, imaging and vision algorithms, wireless network and human-machine interface problems. Due to the limitation of computing capacity that early mobile devices have, researchers proposed client-server module, which push the data to more powerful computing platforms through wireless network, and let the cloud or standalone servers carry out all the computing and processing work. This thesis reviewed the development of mobile hardware and software platform, and the related research done on mobile imaging for the past 20 years. There are several researches on mobile imaging, but few people aim at building a framework which helps engineers solving problems by using mobile imaging. With higher-resolution imaging and high-performance computing power built into smart mobile devices, more and more imaging processing tasks can be achieved on the device rather than the client-server module. Based on this fact, a framework of collaborative mobile imaging is introduced for civil infrastructure condition assessment to help engineers solving technical challenges. Another contribution in this thesis is applying mobile imaging application into home automation. E-SAVE is a research project focusing on extensive use of automation in conserving and using energy wisely in home automation. Mobile users can view critical information such as energy data of the appliances with the help of mobile imaging. OpenCV is an image processing and computer vision library. The applications in this thesis use functions in OpenCV including camera calibration, template matching, image stitching and Canny edge detection. The application aims to help field engineers is interactive crack detection. The other one uses template matching to recognize appliances in the home automation system.eng
dc.description.tableofcontentsIntroduction -- Background and related work -- Basic imaging processing methods for mobile applications -- Collaborative and interactive mobile imaging -- Mobile imaging for smart energy -- Conclusion and recommendationseng
dc.format.extentxi, 83 pageseng
dc.identifier.urihttp://hdl.handle.net/10355/35646eng
dc.subject.lcshApplication softwareeng
dc.subject.lcshAndroid (Electronic resource)eng
dc.subject.lcshComputer visioneng
dc.subject.otherThesis -- University of Missouri--Kansas City -- Engineeringeng
dc.titleA study of smart device-based mobile imaging and implementation for engineering applicationseng
dc.typeThesiseng
thesis.degree.disciplineElectrical Engineering (UMKC)eng
thesis.degree.grantorUniversity of Missouri--Kansas Cityeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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