DSpace at EWHA: Image Segmentation Methods based on Similarity

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DC Field	Value	Language
dc.contributor.advisor	이준엽	-
dc.contributor.author	김민수	-
dc.creator	김민수	-
dc.date.accessioned	2016-08-25T04:08:31Z	-
dc.date.available	2016-08-25T04:08:31Z	-
dc.date.issued	2005	-
dc.identifier.other	OAK-000000010282	-
dc.identifier.uri	https://dspace.ewha.ac.kr/handle/2015.oak/178602	-
dc.identifier.uri	http://dcollection.ewha.ac.kr/jsp/common/DcLoOrgPer.jsp?sItemId=000000010282	-
dc.description.abstract	Image segmentation generally is a key step in image analysis. In this paper, we will study image segmentation founded on similarity. The principal approaches in the similarity are based on thresholding and region growing by pixel aggregation and by splitting and merging. We understand some basic concepts of various methods and overview how each method is accomplished.	-
dc.description.tableofcontents	Contents 1 Introduction = 1 2 Thresholding = 3 2.1 Fundamentals = 3 2.2 Simple Global Thresholding = 6 2.3 Optimal Thresholding = 6 Chapter 3 Region Growing = 11 3.1 Basic Formulation = 12 3.2 Region Growing by Pixel Aggregation = 12 3.3 Region Growing by Splitting and Merging = 14 Chapter 4 Concluding Remarks = 18 Bibliography = 20	-
dc.format	application/pdf	-
dc.format.extent	309811 bytes	-
dc.language	eng	-
dc.publisher	이화여자대학교 대학원	-
dc.subject	Image segmentation	-
dc.subject	Thresholding	-
dc.subject	Region growing	-
dc.subject	Region splitting and merging	-
dc.title	Image Segmentation Methods based on Similarity	-
dc.type	Master's Thesis	-
dc.creator.othername	Kim, Minsu	-
dc.format.page	ii, 20 p.	-
dc.identifier.thesisdegree	Master	-
dc.identifier.major	대학원 수학과	-
dc.date.awarded	2005. 8	-