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논문 기본 정보

자료유형
학술저널
저자정보
DULTUYA TERBISH (NATIONAL UNIVERSITY OF MONGOLIA) MYUNGJOO KANG (SEOUL NATIONAL UNIVERSITY)
저널정보
한국산업응용수학회 JOURNAL OF THE KOREAN SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS Journal of the Korean Society for Industrial and Applied Mathematics Vol.18 No.3
발행연도
2014.9
수록면
225 - 244 (20page)

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초록· 키워드

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In this work, we discuss segmentation algorithms based on the level set method that incorporates shape prior knowledge. Fundamental segmentation models fail to segment desirable objects from a background when the objects are occluded by others or missing parts of their whole. To overcome these difficulties, we incorporate shape prior knowledge into a new segmentation energy that, uses global and local image information to construct the energy functional. This method improves upon other methods found in the literature and segments images with intensity inhomogeneity, even when images have missing or misleading information due to occlusions, noise, or low-contrast. We consider the case when the shape prior is placed exactly at the locations of the desired objects and the case when the shape prior is placed at arbitrary locations. We test our methods on various images and compare them to other existing methods. Experimental results show that our methods are not only accurate and computationally efficient, but faster than existing methods as well.

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ABSTRACT
1. INTRODUCTION
2. RELATED WORKS
3. PROPOSED MODELS
4. EXPERIMENTAL RESULTS
5. CONCLUSION
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UCI(KEPA) : I410-ECN-0101-2015-400-002538191