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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Automated Segmentation and Tracking of SAM Cells
verfasst von : Min Liu, Peng Xiang
Erschienen in: Pattern Recognition
Verlag: Springer Berlin Heidelberg
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In this paper, we propose an automated segmentation and tracking system for the shoot apical meristem (SAM) cells. Cells are segmented using a mixed filter based watershed segmentation method, which is proved to be very robust and efficient. After segmentation, a Triangle Neighborhood Structure matching method is proposed to track the segmented cells across different time instances. Our tracking method reduces the dependence on neighbors, because we only need two neighbors for any cells for matching while the other local graph matching methods require a much larger number of neighbors. Using our proposed segmentation and tracking system, we are able to track 97% of the plant SAM cells.