Cell detection and tracking for micromanipulation vision system of cell-operation robot

This paper discusses cell detection and tracking in the microscope scene for a cell-operation robot. An approach integrating morphological operator and Bayesian estimation technique is used for cell detection and tracking. One of the problems in the implementation is a difficulty in obtaining accurate information of cells. We introduce classification criterion, which rely on both shape and texture information of the cell to get fine result, and present geometric constraints incorporating nonlinear diffusion process to reduce drift of the point:; during the tracking procedure. A preliminary test is conducted to the system. Experimental results show the effectiveness of the proposed methods.