DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Chang Ock | - |
dc.contributor.advisor | 이창옥 | - |
dc.contributor.author | Yeo, Doyeob | - |
dc.contributor.author | 여도엽 | - |
dc.date.accessioned | 2018-05-23T19:35:44Z | - |
dc.date.available | 2018-05-23T19:35:44Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=718853&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/241912 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 수리과학과, 2017.8,[v, 35 p. :] | - |
dc.description.abstract | In general images, it is practically hard to distinguish only the desired object using the conventional image segmentation methods. In many cases, we can segment the desired object by using the shape information of the object in addition to the standard image segmentation. Chan and Zhu's work produces wrong results depending on intensities of objects. In this paper, we propose a novel model for the shape prior segmentation that produces robust results using the hierarchical image segmentation and an attraction term. Moreover, we adopt an image registration technique and a multi-region image segmentation to get an initial for a given shape prior.Finally, we consider the free-form deformation in obtaining the shape function from the reference shape prior for real-world images. Numerical experiments demonstrate the results independent of intensities of objects and the location of the reference shape prior. All numerical calculations are automatic and progress without any user input. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | shape prior segmentation▼ahierarchical image segmentation▼aimage registration▼afree-form deformation | - |
dc.subject | 주어진 형상 정보를 이용한 영상 분할▼a계층구조의 영상 분할▼a영상 정합▼a자유 형상 변형 | - |
dc.title | Design of an energy functional and an initial curve for the shape prior segmentation | - |
dc.title.alternative | 주어진 형상 정보를 이용한 영상 분할에서의 에너지 범함수 설계와 초기값 설정 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :수리과학과, | - |
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