提出利用均衡化特征匹配来进行非刚性细胞形体跟踪的方法。采用重启动的随机游走方法建立并求解特征匹配概率模型,利用双向均衡方法对匹配邻接矩阵进行均衡化处理,得到指定目标与待跟踪目标之间的精确匹配,以获得目标的定位跟踪结果。同时利用特征匹配结果进行目标的自动标定,并应用图像分割方法进行目标的精确轮廓跟踪。实验结果表明,将该方法应用于视频中动态背景下的运动细胞形态跟踪时,在背景相似度较高及目标迅速移动的条件下,表现出了良好的性能,与同类方法相比可获得较高的定位精度以及更为准确的目标轮廓。

A new algorithm of non-rigid cell tracking based on balancing feature matching is proposed. A probabilistic model is established and solved using Random Walks with Restart (RWR). An efficient method for bidirectional balance is presented to balance the adjacency matrix of RWR,and then a precise matching between objects under different deformations is completed. The position tracking is accomplished based on the matching results. At the same time,an automatic calibration to object is presented with the results of the feature matching. A precise object contour tracking is presented with a method for image segmentation. We prove by experiment that the method shows good performance in the conditions of high background similarity and fast moving objects when used for tracking moving cell under dynamic background in videos. More accurate localization and target contour description can be obtained compared with other methods.