Optic Flow Based Occlusion Analysis for Cell Division Detection

  • Sha Yu
  • Derek Molloy
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 291)


The computer vision domain has seen increasing attention in the design of automated tools for cellular biology researchers. In addition to quantitative analysis on whole populations of cells, identification of the cell division events is another important topic. In this research, a novel fully automated image-based cell-division-detection approach is proposed. Differing from most of the existing approaches that exploit training-based or image-based segmentation methods, the main idea of the proposed approach is detecting cell divisions using a motion based occlusion analysis process. Testing has been performed on different types of cellular datasets, including fluorescence images and phase-contrast data, and it has confirmed the effectiveness of the proposed method.


Motion estimation Optic flow Cell division detection Occlusion detection Forward–backward motion consistency 



This research was supported by the National Biophotonics Imaging Platform (NBIP) Ireland funded under the Higher Education Authority PRTLI Cycle 4, co-funded by the Irish Government and the European Union—Investing in your future.


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Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  1. 1.Centre for Image Processing and Analysis (CIPA)Dublin City UniversityDublin 9Ireland

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