Study on method of tracking the active cells in image sequences based on EKF-PF.
- Author:
Chunming TANG
1
;
Ying LIU
Author Information
1. College of Information and Communication Engineering of Harbin Engineering University, Harbin 150001, China. tangchunming@hrbeu.edu.cn
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Cell Movement;
Cell Tracking;
methods;
Forecasting;
Image Enhancement;
methods;
Image Interpretation, Computer-Assisted;
methods;
Models, Theoretical
- From:
Journal of Biomedical Engineering
2013;30(1):6-11
- CountryChina
- Language:Chinese
-
Abstract:
In cell image sequences, due to the nonlinear and nonGaussian motion characteristics of active cells, the accurate prediction and tracking is still an unsolved problem. We applied extended Kalman particle filter (EKF-PF) here in our study, attempting to solve the problem. Firstly we confirmed the existence and positions of the active cells. Then we established a motion model and improved it via adding motion angle estimation. Next we predicted motion parameters, such as displacement, velocity, accelerated velocity and motion angle, in region centers of the cells being tracked. Finally we obtained the motion traces of active cells. There were fourteen active cells in three image sequences which have been tracked. The errors were less than 2.5 pixels when the prediction values were compared with actual values. It showed that the presented algorithm may basically reach the solution of accurate predition and tracking of the active cells.
