[-] Show simple item record

dc.contributor.advisorShyu, Chi-Reneng
dc.contributor.authorHao, Dayangeng
dc.date.issued2008eng
dc.date.submitted2008 Summereng
dc.descriptionThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from title screen of research.pdf file (viewed on August 12, 2009)eng
dc.descriptionThesis (M.S.) University of Missouri-Columbia 2008.eng
dc.description.abstractIn recent years, automatic content extraction, analysis and retrieval for plant visual trait studies play a more important role than ever before, because traditional manual processing suffers two major issues: excessive processing time and subjectiveness rising from different individuals. Therefore, to conduct high throughput experiments, plant biologists are in urgent need for, 1) efficient computer software to automatically extract and analyze significant contents, 2) scoring functions to mimic human scoring, etc. In order to meet these needs, a series of customized computer vision and image processing algorithms is developed in our research. These algorithms are particularly customized for two model plants: Maize lesion extraction and Arabidopsis insect damage calculation. For maize, a mixture of edge-based and region-based segmentation algorithm is developed to extract lesions caused by fungus; for Arabidopsis, a top-down segmentation process is employed to measure leaf area differences resulting from insect damage. Our informatics tools can be generalized to accommodate a broad range of plant species for visual trait studies. Moreover, they will potentially provide a framework for cross-institutional and collaborative studies.eng
dc.description.bibrefIncludes bibliographical referenceseng
dc.identifier.merlinb70624136eng
dc.identifier.oclc430219043eng
dc.identifier.urihttps://doi.org/10.32469/10355/5704eng
dc.identifier.urihttps://hdl.handle.net/10355/5704
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri-Columbia. Graduate School. Theses and Dissertations. Theses. 2008 Theseseng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subject.lcshCorn -- Diseases and pests -- Monitoring -- Data processingeng
dc.subject.lcshArabidopsis -- Diseases and pests -- Monitoring -- Data processingeng
dc.subject.lcshData miningeng
dc.subject.lcshInformation visualizationeng
dc.titleContent extraction, analysis, and retrieval for plant visual traits studieseng
dc.typeThesiseng
thesis.degree.disciplineComputer science (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


Files in this item

[PDF]
[PDF]
[PDF]

This item appears in the following Collection(s)

[-] Show simple item record