Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/277525
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dc.coverage.spatial
dc.date.accessioned2020-02-18T05:32:16Z-
dc.date.available2020-02-18T05:32:16Z-
dc.identifier.urihttp://hdl.handle.net/10603/277525-
dc.description.abstractIn today s health care, Image Segmentation (IS) is a research area in which the researchers are continuously undergoing various inventions. Image Segmentation is one newlineof the most stimulating and difficult problem in image processing, which is used in a newlinevariety of applications such as computer vision, object recognition and medical imaging. newlineMedical imaging is tough to identify and segment the images, which contains newlinecomplex color, texture and orientation of cells in their structure. While performing newlinewith Medical Image Segmentation (MIS), the problems arises like overlapping of images, newlineirregular background subtraction, noise and low contrast etc. In order to overcome newlinethese difficulties, an improved segmentation and classification algorithms are employed. newline
dc.format.extent95
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleA Pattern Recognition approach to image Segmentation using Clustering Methods
dc.title.alternative
dc.creator.researcherHEMALATHA. K.L.
dc.subject.keywordEngineering and Technology,Computer Science, Pattern Recognition, Clustering Methods
dc.description.note
dc.contributor.guideSUNILKUMAR S. MANVI
dc.publisher.placeBengaluru
dc.publisher.universityReva University
dc.publisher.institutionSchool of Computing and Information Technology
dc.date.registered2014
dc.date.completed2017
dc.date.awarded2017
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:School of Computing and Information Technology

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01_title.pdfAttached File74.62 kBAdobe PDFView/Open
02_declaration.pdf57.21 kBAdobe PDFView/Open
03_acknoweledgements.pdf53.22 kBAdobe PDFView/Open
04_table of contents.pdf52.6 kBAdobe PDFView/Open
05_list of tables.pdf51.2 kBAdobe PDFView/Open
06_abbreviations.pdf52.88 kBAdobe PDFView/Open
07_abstarct.pdf52.76 kBAdobe PDFView/Open
08_chapter.1.pdf249.06 kBAdobe PDFView/Open
09_chapter.2.pdf118 kBAdobe PDFView/Open
10_chapter.3.pdf152.05 kBAdobe PDFView/Open
11_chapter.4.pdf203.42 kBAdobe PDFView/Open
12_chapter.5.pdf544.62 kBAdobe PDFView/Open
13_chapter.6.pdf70.37 kBAdobe PDFView/Open
14_references.pdf108.46 kBAdobe PDFView/Open
15_publications.pdf50.33 kBAdobe PDFView/Open


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