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Journal of The Korea Society of Computer and Information 2021 KCI Impact Factor : 0.62

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Complex Cell Image Segmentation via Structural Feature Information

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2012, 17(10), pp.35-41

Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

kim Seong-Kon ¹

¹부산가톨릭대학교

ABSTRACT
열림/닫힘 버튼

We propose a new marker driven Watershed algorithm for automated segmentation of clustered cell from microscopy image with less over segmentation. The Watershed Transform is able to segment extremely complex objects which are highly touched and overlapped each other. The success of the Watershed Transform depends essentially on the finding markers for each of the objects of interest. For extracting of markers positioning around center of each cell we used radial symmetry and iterative voting algorithms. With synthetic and real images, we quantitatively demonstrate the performance of our method and achieved better results than the other compared methods.
KEYWORDS
열림/닫힘 버튼

Watershed Algorithms, Radial Symmetry, Iterative Voting, Marker

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* 2021년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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