Centroid tracking and velocity measurement of white blood cell in video

  • Mohamed Maher Ata
  • Amira S. Ashour
  • Yanhui Guo
  • Mustafa M. Abd Elnaby
Part of the following topical collections:
  1. Special Issue on Application of Artificial Intelligence in Health Research


Automated blood cells tracking system has a vital role as the tracking process reflects the blood cell characteristics and indicates several diseases. Blood cells tracking is challenging due to the non-rigid shapes of the blood cells, and the variability in their videos along with the existence of different moving objects in the blood. To tackle such challenges, we proposed a green star based centroid (GSBC) moving white blood cell (WBC) tracking algorithm to measure its velocity and draw its trajectory. The proposed cell tracking system consists of two stages, namely WBC detection and blob analysis, and fine tuning the tracking process by determine the centroid of the WBC, and mark the centroid for further fine tracking and to exclude the bacteria from the bounding box. Furthermore, the speed and the trajectory of the WBC motion are recorded and plotted. In the experiments, an optical flow technique is compared with the proposed tracking system showing the superiority of the proposed system as the optical flow method failed to track the WBC. The proposed system identified the WBC accurately, while the optical flow identified all other objects lead to its disability to track the WBC.


White blood cell Cell detection Velocity measurements Trajectory analysis Video processing Blob analysis Tracking system 



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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Misr Higher Institute of Engineering and TechnologyMansouraEgypt
  2. 2.Department of Electronics and Electrical Communications Engineering, Faculty of EngineeringTanta UniversityTantaEgypt
  3. 3.Department of Computer ScienceUniversity of Illinois at SpringfieldSpringfieldUSA

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