Separating Algorithm for Cell Image Based on Boundary-Stripped
基于边界剥离的细胞图象分离算法

The clustering phenomenon often appears in the cell image auto reading system, i.e., some cells overlap or touch together to form a big area. It is necessary to design an effective algorithm to separate the clustering cells into single ones. Most of the existed separating algorithms are based on two hypotheses: 1) at points where cells touch, the cluster boundary tends to form an acute angle; 2) at points where the cells touch, the optical density is relatively low, otherwise it will be very difficult to separate them properly. But in the actual cell images, the two hypotheses are very difficult to be met. To solve this problem, an algorithm based on boundary stripped is presented in the paper. The boundary of clustering cells is stripped layer by layer in the algorithm. During stripping, judgement is made to determine whether the splitting has happened, and then the actual separation is taken in the original cell image. It does not require the clustering cells should necessarily meet the two hypotheses. The experiment result shows that the algorithm is effective.