Browse

Image segmentation using the level set method by the data clustering algorithm
레벨셋 함수와 데이터 군집화 방법을 이용한 영상분할에 대한 연구

DC Field Value Language
dc.contributor.advisor강명주-
dc.contributor.author김연후-
dc.date.accessioned2017-07-19T08:58:44Z-
dc.date.available2017-07-19T08:58:44Z-
dc.date.issued2013-02-
dc.identifier.other000000010006-
dc.identifier.urihttp://hdl.handle.net/10371/131467-
dc.description학위논문 (석사)-- 서울대학교 대학원 : 수리과학부, 2013. 2. 강명주.-
dc.description.abstractThis paper discusses a variational method for image segmentation by using the level set method with data clustering algorithm. The traditional method of image segmentation has been to separate the given image into two regions-inside and outside. But in the multi-phase segmentation problem, the result is considerably different depending on the number of phases which is given a priori by the user. Therefore, choosing the exact phase number is a critical decision in the multi-phase image segmentation. In this study, we investigated the previous image segmentation models. Then, a multi-phase
segmentation method using data clustering algorithms on the image histogram is presented. This study analyzed previous algorithms by giving some changes on the algorithm, and determined the phase number by applying new segmentation method and data clustering methods. Finally, some numerical results were shown for various images.
-
dc.description.tableofcontentsContents

Abstract (i)
1 Intoduction (1)
2 The Segmentation Using The Level Set Method (3)
2.1 Mumford-Shah Functional . . . . . . . . . . . . . . . . . . . . (3)
2.2 Level Set Formulation: The Chan-Vese Segmentation Model . (4)
2.3 Connection to k-means Clustering: Gibou-Fedkiw Model . . . (7)

3 Adaptive Global Maximum Clustering Algorithm and Its Segmentation
Model (9)
3.1 Multiphase Image Segmentation . . . . . . . . . . . . . . . . . (9)
3.2 Adaptive Global Maximum Clustering Algorithm . . . . . . . (10)
3.3 The Segmentation Model . . . . . . . . . . . . . . . . . . . . . (12)

4 Results of Our Approach (15)
4.1 Determining the Initial μ of the k-means Clustering . . . . . . (15)
4.2 Revising the Algorithm Using Another Clustering Method Instead of the k-means Clustering . . . . . . . . . . . . . . . . . (20)

Abstract (in Korean) (28)
-
dc.formatapplication/pdf-
dc.format.extent798395 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectbasic global thresholding-
dc.subjectimage segmentation-
dc.subjectk-means clustering-
dc.subjectlevel set method-
dc.subjectvariational method-
dc.subject.ddc510-
dc.titleImage segmentation using the level set method by the data clustering algorithm-
dc.title.alternative레벨셋 함수와 데이터 군집화 방법을 이용한 영상분할에 대한 연구-
dc.typeThesis-
dc.description.degreeMaster-
dc.citation.pages35-
dc.contributor.affiliation자연과학대학 수리과학부-
dc.date.awarded2013-02-
Appears in Collections:
College of Natural Sciences (자연과학대학)Dept. of Mathematical Sciences (수리과학부)Theses (Master's Degree_수리과학부)
Files in This Item:
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse